From df6ba0d4dd7d938a507be7270dfa81d24a6a854a Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Thu, 10 Sep 2020 00:30:14 +0200
Subject: [PATCH] [Notebook] update end2end notebooks to use ZynqBuild
---
.../end2end_example/cnv_end2end_example.ipynb | 987 +++++++++++++++---
.../finn-design-flow-example.svg | 2 +-
.../end2end_example/tfc_end2end_example.ipynb | 883 ++--------------
3 files changed, 927 insertions(+), 945 deletions(-)
diff --git a/notebooks/end2end_example/cnv_end2end_example.ipynb b/notebooks/end2end_example/cnv_end2end_example.ipynb
index c1ae0caea..e0f346eb2 100644
--- a/notebooks/end2end_example/cnv_end2end_example.ipynb
+++ b/notebooks/end2end_example/cnv_end2end_example.ipynb
@@ -55,7 +55,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
@@ -76,20 +76,9 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 5,
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Downloading: \"https://github.com/Xilinx/brevitas/releases/download/bnn_pynq-r0/cnv_1w1a-758c8fef.pth\" to /home/maltanar/.cache/torch/checkpoints/cnv_1w1a-758c8fef.pth\n",
- "100%|██████████| 6227617/6227617 [00:01<00:00, 4429264.32it/s]\n",
- "/workspace/brevitas/brevitas_examples/bnn_pynq/models/CNV.py:107: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.\n",
- " x = 2.0 * x - torch.tensor([1.0], device=x.device)\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"import onnx\n",
"from finn.util.test import get_test_model_trained\n",
@@ -120,7 +109,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
@@ -144,10 +133,10 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f7b24ef8b00>"
+ "<IPython.lib.display.IFrame at 0x7fc303685940>"
]
},
- "execution_count": 3,
+ "execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
@@ -181,7 +170,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
@@ -217,7 +206,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
@@ -243,10 +232,10 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f0cb1098f28>"
+ "<IPython.lib.display.IFrame at 0x7fc295ad28d0>"
]
},
- "execution_count": 5,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -266,7 +255,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
@@ -276,6 +265,7 @@
")\n",
"from finn.transformation.move_reshape import RemoveCNVtoFCFlatten\n",
"from finn.custom_op.registry import getCustomOp\n",
+ "from finn.transformation.infer_data_layouts import InferDataLayouts\n",
"\n",
"# choose the memory mode for the MVTU units, decoupled or const\n",
"mem_mode = \"decoupled\"\n",
@@ -287,6 +277,8 @@
"model = model.transform(to_hls.InferStreamingMaxPool())\n",
"# get rid of Reshape(-1, 1) operation between hlslib nodes\n",
"model = model.transform(RemoveCNVtoFCFlatten())\n",
+ "# infer tensor data layouts\n",
+ "model = model.transform(InferDataLayouts())\n",
"parent_model = model.transform(CreateDataflowPartition())\n",
"parent_model.save(build_dir + \"/end2end_cnv_w1a1_dataflow_parent.onnx\")\n",
"sdp_node = parent_model.get_nodes_by_op_type(\"StreamingDataflowPartition\")[0]\n",
@@ -306,7 +298,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
@@ -332,10 +324,10 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f0cb063e208>"
+ "<IPython.lib.display.IFrame at 0x7fc295ec6f60>"
]
},
- "execution_count": 7,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
@@ -353,14 +345,10 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
- "from finn.transformation.fpgadataflow.insert_dwc import InsertDWC\n",
- "from finn.transformation.fpgadataflow.insert_tlastmarker import InsertTLastMarker\n",
- "from finn.transformation.fpgadataflow.insert_fifo import InsertFIFO\n",
- "\n",
"model = ModelWrapper(build_dir + \"/end2end_cnv_w1a1_dataflow_model.onnx\")\n",
"fc_layers = model.get_nodes_by_op_type(\"StreamingFCLayer_Batch\")\n",
"# each tuple is (PE, SIMD, in_fifo_depth) for a layer\n",
@@ -388,9 +376,6 @@
" simd = folding[i][1]\n",
" swg_inst.set_nodeattr(\"SIMD\", simd)\n",
"\n",
- "model = model.transform(InsertDWC())\n",
- "model = model.transform(InsertFIFO())\n",
- "model = model.transform(InsertTLastMarker())\n",
"model = model.transform(GiveUniqueNodeNames())\n",
"model.save(build_dir + \"/end2end_cnv_w1a1_folded.onnx\")"
]
@@ -404,7 +389,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -430,10 +415,10 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f0cb1098748>"
+ "<IPython.lib.display.IFrame at 0x7fc295b3d3c8>"
]
},
- "execution_count": 9,
+ "execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
@@ -455,94 +440,21 @@
"source": [
"## 4. Hardware Generation\n",
"\n",
- "From this point onward, the steps we have to follow do not depend on the particular network and will be exactly the same as the TFC-w1a1 example. We first proceed with HLS synthesis, **which may take 10-20 minutes depending on your host computer**."
+ "From this point onward, the steps we have to follow do not depend on the particular network and will be exactly the same as the TFC-w1a1 example. **which may take about 30 minutes depending on your host computer**."
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
- "from finn.transformation.fpgadataflow.prepare_ip import PrepareIP\n",
- "from finn.transformation.fpgadataflow.hlssynth_ip import HLSSynthIP\n",
- "from finn.util.basic import pynq_part_map\n",
- "\n",
"test_pynq_board = \"Pynq-Z1\"\n",
- "test_fpga_part = pynq_part_map[test_pynq_board]\n",
- "target_clk_ns = 5\n",
- "\n",
- "model = ModelWrapper(build_dir + \"/end2end_cnv_w1a1_folded.onnx\")\n",
- "model = model.transform(PrepareIP(test_fpga_part, target_clk_ns))\n",
- "model = model.transform(HLSSynthIP())\n",
- "model.save(build_dir + \"/end2end_cnv_w1a1_ipgen.onnx\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Once the HLS synthesis is complete, we can stitch together the generated IP blocks into a larger IP that is the implementation of our network:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {},
- "outputs": [],
- "source": [
- "from finn.transformation.fpgadataflow.replace_verilog_relpaths import (\n",
- " ReplaceVerilogRelPaths,\n",
- ")\n",
- "from finn.transformation.fpgadataflow.create_stitched_ip import CreateStitchedIP\n",
- "\n",
- "model = ModelWrapper(build_dir + \"/end2end_cnv_w1a1_ipgen.onnx\")\n",
- "model = model.transform(ReplaceVerilogRelPaths())\n",
- "model = model.transform(CreateStitchedIP(test_fpga_part))\n",
- "model.save(build_dir + \"/end2end_cnv_w1a1_ipstitch.onnx\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Finally, we create a PYNQ project that includes the hardware \"shell\" that will support our accelerator, including the data movers, and run Vivado synthesis, **which may take around 30 minutes depending on your host computer.**\n",
+ "target_clk_ns = 10\n",
"\n",
- "*If you'd like to watch the progress, you can open the generated project file (printed below) with the Vivado GUI.*"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Vivado synthesis project is at /tmp/finn_dev_maltanar/vivado_pynq_proj_96qtjweo/resizer.xpr\n"
- ]
- }
- ],
- "source": [
- "from finn.transformation.fpgadataflow.make_pynq_proj import MakePYNQProject\n",
- "from finn.transformation.fpgadataflow.synth_pynq_proj import SynthPYNQProject\n",
- "\n",
- "model = ModelWrapper(build_dir + \"/end2end_cnv_w1a1_ipstitch.onnx\")\n",
- "model = model.transform(MakePYNQProject(test_pynq_board))\n",
- "vivado_proj = model.get_metadata_prop(\"vivado_pynq_proj\")\n",
- "print(\"Vivado synthesis project is at %s/resizer.xpr\" % vivado_proj)\n",
- "model.save(build_dir + \"/end2end_cnv_w1a1_pynqproj.onnx\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [],
- "source": [
- "model = ModelWrapper(build_dir + \"/end2end_cnv_w1a1_pynqproj.onnx\")\n",
- "model = model.transform(SynthPYNQProject())\n",
+ "from finn.transformation.fpgadataflow.make_zynq_proj import ZynqBuild\n",
+ "model = ModelWrapper(build_dir+\"/end2end_cnv_w1a1_folded.onnx\")\n",
+ "model = model.transform(ZynqBuild(platform = test_pynq_board, period_ns = target_clk_ns))\n",
"model.save(build_dir + \"/end2end_cnv_w1a1_synth.onnx\")"
]
},
@@ -557,42 +469,839 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
- "from finn.transformation.fpgadataflow.make_pynq_driver import MakePYNQDriver\n",
"from finn.transformation.fpgadataflow.make_deployment import DeployToPYNQ\n",
"\n",
"# set up the following values according to your own environment\n",
"# FINN will use ssh to deploy and run the generated accelerator\n",
- "ip = os.getenv(\"PYNQ_IP\", \"192.168.1.99\")\n",
+ "ip = os.getenv(\"PYNQ_IP\", \"192.168.2.99\")\n",
"username = os.getenv(\"PYNQ_USERNAME\", \"xilinx\")\n",
"password = os.getenv(\"PYNQ_PASSWORD\", \"xilinx\")\n",
"port = os.getenv(\"PYNQ_PORT\", 22)\n",
- "target_dir = os.getenv(\"PYNQ_TARGET_DIR\", \"/home/xilinx/finn\")\n",
+ "target_dir = os.getenv(\"PYNQ_TARGET_DIR\", \"/home/xilinx/finn_cnv_end2end_example\")\n",
"\n",
"model = ModelWrapper(build_dir + \"/end2end_cnv_w1a1_synth.onnx\")\n",
- "model = model.transform(MakePYNQDriver(platform=\"zynq\"))\n",
"model = model.transform(DeployToPYNQ(ip, port, username, password, target_dir))\n",
"model.save(build_dir + \"/end2end_cnv_w1a1_pynq_deploy.onnx\")"
]
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_01nxn6ne:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9171 Aug 28 01:28 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 01:28 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 28 01:29 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 01:29 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 01:28 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 01:28 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 01:29 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_06f3kimz:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 27 13:30 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 13:30 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 27 13:45 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 13:45 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 13:30 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 27 13:30 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 13:45 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_06t_joa5:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 28 16:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 16:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 28 16:12 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 16:12 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 16:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 28 16:11 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 16:12 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_0qvh6x0y:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 29 04:50 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 04:50 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 29 04:50 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 04:51 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 04:50 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 29 04:50 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 04:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_1axnzb_3:\r\n",
+ "total 4288\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9230 Aug 21 09:39 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 21 09:39 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 21 09:39 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 21 09:40 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 21 09:39 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301904 Aug 21 09:39 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 21 09:40 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_21w59oae:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 29 04:50 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 04:50 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 29 04:51 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 04:51 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 04:50 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 29 04:50 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 04:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_28bro9rw:\r\n",
+ "total 4220\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9409 Sep 4 03:35 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 03:35 finn\r\n",
+ "-rw-r--r-- 1 root root 207 Sep 4 03:39 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 03:35 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 03:35 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Sep 4 03:39 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_3_7bkkrt:\r\n",
+ "total 4272\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9153 Aug 30 10:55 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 30 10:55 finn\r\n",
+ "-rw-r--r-- 1 root root 205 Aug 30 10:55 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 30 10:55 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301916 Aug 30 10:55 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 30 10:55 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_3tl3zhf1:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8827 Aug 19 10:38 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 10:38 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 19 10:38 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 10:38 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 10:38 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 19 10:38 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 10:38 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_4cf4kfxo:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9172 Aug 29 04:50 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 04:50 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 29 04:51 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 04:51 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 04:50 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 29 04:50 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 04:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment__6inegxp:\r\n",
+ "total 4260\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9147 Aug 30 09:52 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 30 09:52 finn\r\n",
+ "-rw-r--r-- 1 root root 206 Aug 30 09:54 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 30 09:52 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 287145 Aug 30 09:52 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 30 09:54 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_7887i7c6:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9172 Aug 28 01:28 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 01:28 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 28 01:28 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 01:28 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 01:28 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 01:28 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 01:28 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_7co5tvv7:\r\n",
+ "total 4272\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8826 Aug 19 08:34 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 08:34 finn\r\n",
+ "-rw-r--r-- 1 root root 205 Aug 19 08:35 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 08:34 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301916 Aug 19 08:34 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 08:35 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_7rx94isg:\r\n",
+ "total 4228\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 30 12:29 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 30 12:29 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 30 12:29 input.npy\r\n",
+ "-rw-r--r-- 1 root root 205 Aug 30 12:49 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 30 12:30 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 30 12:29 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 30 12:29 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 30 12:49 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_7uu4dz03:\r\n",
+ "total 4240\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9172 Aug 29 16:14 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 16:14 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 29 16:14 input.npy\r\n",
+ "-rw-r--r-- 1 root root 205 Aug 29 16:50 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 16:14 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 16:14 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 29 16:14 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 16:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_81y7pbz6:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8827 Aug 19 00:36 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 00:36 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 19 00:36 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 00:36 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 00:36 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246647 Aug 19 00:36 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 00:36 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_8oclwrec:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 28 16:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 16:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 28 16:11 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 16:11 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 16:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 16:11 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 16:11 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_8xmofsvg:\r\n",
+ "total 4228\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9219 Aug 16 13:19 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 16 13:19 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 16 13:19 input.npy\r\n",
+ "-rw-r--r-- 1 root root 204 Aug 16 13:43 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 16 13:19 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 16 13:19 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246647 Aug 16 13:19 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 16 13:43 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_901qgs6r:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 27 06:06 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 06:06 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 27 06:06 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 06:06 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 06:06 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 27 06:06 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 06:06 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_93g2nqtq:\r\n",
+ "total 4260\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8820 Aug 19 07:32 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 07:32 finn\r\n",
+ "-rw-r--r-- 1 root root 203 Aug 19 07:35 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 07:32 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 287145 Aug 19 07:32 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 07:35 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_9ksrgg2h:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8820 Aug 19 07:42 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 07:42 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 144 Aug 19 07:42 input.npy\r\n",
+ "-rw-r--r-- 1 root root 96 Aug 19 07:42 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 07:42 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246209 Aug 19 07:42 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 07:42 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_a6wquogd:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9171 Aug 28 01:28 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 01:28 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 28 01:28 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 01:28 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 01:28 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 01:28 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 01:28 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ale2myrj:\r\n",
+ "total 4276\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8819 Aug 19 09:47 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 09:47 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 19 09:47 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 09:47 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 09:47 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301911 Aug 19 09:47 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 09:47 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ao3q4u89:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 27 15:49 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 15:49 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 27 23:39 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 23:39 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 15:49 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 27 15:49 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 23:39 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_cam682qh:\r\n",
+ "total 4220\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9389 Sep 4 03:35 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 03:35 finn\r\n",
+ "-rw-r--r-- 1 root root 204 Sep 4 03:38 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 03:35 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Sep 4 03:35 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Sep 4 03:38 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_diprgb3z:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8841 Aug 20 02:05 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 20 02:05 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 20 04:11 input.npy\r\n",
+ "-rw-r--r-- 1 root root 84 Aug 20 04:12 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 20 02:05 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246207 Aug 20 02:05 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 20 04:12 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment__e5pd_a_:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9172 Aug 27 05:50 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 05:50 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 27 05:51 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 05:51 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 05:50 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 27 05:50 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 05:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ecyflrb3:\r\n",
+ "total 4212\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 29 13:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 13:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 13:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 29 13:11 resizer.hwh\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_eh6_czd4:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9171 Aug 28 16:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 16:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 28 16:12 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 16:12 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 16:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 16:11 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 16:12 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_f_bruffc:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9219 Aug 15 11:46 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 15 11:46 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 15 11:46 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 15 11:46 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 15 11:46 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 15 11:46 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 15 11:46 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_fgopkgby:\r\n",
+ "total 4272\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9153 Aug 29 15:17 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 15:17 finn\r\n",
+ "-rw-r--r-- 1 root root 203 Aug 29 15:17 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 29 15:17 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301916 Aug 29 15:17 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 15:17 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_fu_jf95u:\r\n",
+ "total 4220\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9408 Sep 4 03:35 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 03:35 finn\r\n",
+ "-rw-r--r-- 1 root root 205 Sep 4 03:40 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 03:35 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 03:35 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Sep 4 03:40 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_gsss7jov:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9171 Aug 29 04:50 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 04:50 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 29 04:51 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 04:51 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 04:50 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 29 04:50 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 04:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_h8o7knmw:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9147 Aug 29 14:19 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 14:19 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 144 Aug 29 14:19 input.npy\r\n",
+ "-rw-r--r-- 1 root root 96 Aug 29 14:19 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 14:19 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246209 Aug 29 14:19 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 14:19 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_i705jzvl:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 29 04:50 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 04:50 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 29 04:51 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 04:51 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 04:50 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 29 04:50 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 04:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_i7w9f7gi:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9171 Aug 29 04:50 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 04:50 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 29 04:51 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 04:52 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 04:50 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 29 04:50 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 04:52 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ih88epbh:\r\n",
"total 4260\r\n",
- "-rw-r--r-- 1 xilinx xilinx 6380 May 7 15:14 driver.py\r\n",
- "drwxr-xr-x 4 xilinx xilinx 4096 May 7 15:14 finn\r\n",
- "-rw-r--r-- 1 xilinx xilinx 4045675 May 7 15:14 resizer.bit\r\n",
- "-rw-r--r-- 1 xilinx xilinx 302015 May 7 15:14 resizer.hwh\r\n"
+ "-rw-r--r-- 1 xilinx xilinx 9147 Aug 29 14:15 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 14:15 finn\r\n",
+ "-rw-r--r-- 1 root root 207 Aug 29 14:18 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 29 14:15 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 287145 Aug 29 14:15 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 14:18 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ii6xl1b5:\r\n",
+ "total 4240\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9237 Aug 16 13:02 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 16 13:02 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 16 13:02 input.npy\r\n",
+ "-rw-r--r-- 1 root root 207 Aug 16 13:45 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 16 13:02 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 16 13:02 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246647 Aug 16 13:02 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 16 13:45 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ilfexhs3:\r\n",
+ "total 4288\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8838 Aug 19 08:57 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 08:57 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 19 08:57 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 08:57 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 08:57 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301904 Aug 19 08:57 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 11:00 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_it7n5qfu:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9172 Aug 27 15:49 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 15:49 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 27 23:40 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 23:40 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 15:49 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 27 15:49 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 23:40 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_iuszsd4p:\r\n",
+ "total 4212\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9409 Sep 4 13:08 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 13:08 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 13:08 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 13:08 resizer.hwh\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_j8ixf__1:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 27 15:49 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 15:49 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 27 23:21 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 23:21 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 15:49 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 27 15:49 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 23:21 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_jdmw5vhc:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9219 Aug 16 02:18 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 16 02:18 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 16 02:19 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 16 02:19 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 16 02:18 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246647 Aug 16 02:18 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 16 02:19 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_jk8k3kdu:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8825 Aug 19 10:56 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 10:56 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 19 10:56 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 10:56 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 10:56 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 19 10:56 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 10:56 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_jlcdo6uh:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8845 Aug 19 00:19 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 00:19 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 19 00:19 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 00:19 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 00:19 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246647 Aug 19 00:19 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 00:19 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ke08eze6:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 25 05:14 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 25 05:14 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 25 05:14 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 25 05:15 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 25 05:14 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 25 05:14 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 25 05:15 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_lga6n0hz:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9172 Aug 28 16:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 16:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 28 16:12 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 16:12 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 16:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 16:11 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 16:12 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_lyzs0vjq:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 29 16:46 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 16:46 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 29 16:46 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 16:46 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 16:46 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 29 16:46 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 16:46 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_n1bf2coh:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 28 07:16 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 07:16 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 28 07:16 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 07:16 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 07:16 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 07:16 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 07:16 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_n6az3jmc:\r\n",
+ "total 4220\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9391 Sep 4 03:35 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 03:35 finn\r\n",
+ "-rw-r--r-- 1 root root 205 Sep 4 03:36 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 03:35 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 03:35 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Sep 4 03:36 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_n_yhs0wi:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9265 Aug 15 04:42 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 15 02:25 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 15 02:25 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 15 04:42 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 15 02:25 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 15 02:25 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 15 04:42 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_om0rv8kw:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9219 Aug 16 02:01 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 16 02:01 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 16 02:01 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 16 02:01 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 16 02:01 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246647 Aug 16 02:01 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 16 02:01 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_p8vv_rbe:\r\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8820 Aug 19 13:19 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 13:19 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 144 Aug 19 13:19 input.npy\r\n",
+ "-rw-r--r-- 1 root root 96 Aug 19 13:19 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 13:19 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246645 Aug 19 13:19 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 13:19 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ph6e_tf5:\r\n",
+ "total 4288\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9229 Aug 21 10:09 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 21 10:09 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 21 10:10 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 21 10:10 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 21 10:09 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301904 Aug 21 10:09 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 21 10:10 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_pt546ihb:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 27 06:25 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 06:25 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 27 06:25 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 06:25 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 06:25 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 27 06:25 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 06:25 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_rkgdftut:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8820 Aug 18 12:54 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 18 12:54 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 144 Aug 18 12:54 input.npy\r\n",
+ "-rw-r--r-- 1 root root 96 Aug 18 12:54 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 18 12:54 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246645 Aug 18 12:54 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 18 12:54 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_rpurccjo:\r\n",
+ "total 4288\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9230 Aug 15 08:31 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 15 08:31 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 15 08:31 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 15 08:31 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 15 08:31 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301904 Aug 15 08:31 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 15 08:31 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_sal6h506:\r\n",
+ "total 4220\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9389 Sep 4 03:35 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 03:35 finn\r\n",
+ "-rw-r--r-- 1 root root 205 Sep 4 03:37 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 03:35 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Sep 4 03:35 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Sep 4 03:37 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_sd_7cw4n:\r\n",
+ "total 4280\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8821 Aug 19 09:36 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 09:36 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 19 09:36 input.npy\r\n",
+ "-rw-r--r-- 1 root root 205 Aug 19 10:58 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 09:36 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 09:36 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301904 Aug 19 09:36 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 10:58 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ss_xv2xy:\r\n",
+ "total 4220\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9408 Sep 4 03:35 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 03:35 finn\r\n",
+ "-rw-r--r-- 1 root root 205 Sep 4 03:40 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 03:35 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 03:35 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Sep 4 03:40 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_t9yxn329:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9212 Aug 16 08:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 16 08:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 144 Aug 16 08:11 input.npy\r\n",
+ "-rw-r--r-- 1 root root 96 Aug 16 08:11 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 16 08:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246645 Aug 16 08:11 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 16 08:11 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_tc39mytd:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9219 Aug 16 05:44 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 16 05:44 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 16 05:44 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 16 05:44 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 16 05:44 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246647 Aug 16 05:44 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 16 05:44 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_tgt4myfy:\r\n",
+ "total 4276\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8814 Aug 19 07:32 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 07:32 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 144 Aug 19 07:32 input.npy\r\n",
+ "-rw-r--r-- 1 root root 96 Aug 19 07:32 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 07:32 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301916 Aug 19 07:32 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 07:32 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_tp9a5_fy:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9171 Aug 28 16:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 16:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 28 16:13 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 16:13 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 16:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 28 16:11 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 16:13 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_tucd1097:\r\n",
+ "total 4228\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 29 16:29 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 29 16:29 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 29 16:29 input.npy\r\n",
+ "-rw-r--r-- 1 root root 206 Aug 29 16:48 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 29 16:29 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 29 16:29 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 29 16:29 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 29 16:48 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ub1tgpmc:\r\n",
+ "total 4228\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9219 Aug 22 12:43 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 22 12:43 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 22 12:43 input.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 120 Aug 23 04:02 output_golden.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 23 04:02 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 22 12:43 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 22 12:43 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 23 04:02 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ucr_973r:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 30 12:47 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 30 12:47 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 30 12:47 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 30 12:47 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 30 12:47 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 30 12:47 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 30 12:47 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_uxodq9a4:\r\n",
+ "total 20\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8820 Aug 19 13:04 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 13:04 finn\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 13:04 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_w0ou6nez:\r\n",
+ "total 4220\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9391 Sep 4 01:13 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 01:13 finn\r\n",
+ "-rw-r--r-- 1 root root 204 Sep 4 01:14 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 01:13 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 01:13 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Sep 4 01:14 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_wr1hljxk:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9219 Aug 15 10:07 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 15 10:07 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 15 10:07 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 15 10:07 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 15 10:07 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 15 10:07 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 15 10:07 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_wvxkayc8:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9152 Aug 28 16:11 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 28 16:11 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 28 16:12 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 28 16:12 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 28 16:11 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246215 Aug 28 16:11 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 28 16:12 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_x1yyq4s3:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9154 Aug 27 15:49 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 27 15:49 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 27 23:07 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 27 23:07 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 27 15:49 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 27 15:49 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 27 23:07 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_xec0no1y:\r\n",
+ "total 4276\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8819 Aug 19 09:59 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 09:59 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 19 09:59 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 09:59 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 09:59 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301911 Aug 19 09:59 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 09:59 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_xf594c4i:\r\n",
+ "total 4288\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8837 Aug 19 09:27 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 09:27 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 19 09:27 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 09:27 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045675 Aug 19 09:27 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 301904 Aug 19 09:27 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 11:02 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_xuytd3ej:\r\n",
+ "total 4236\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8845 Aug 19 10:23 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 10:23 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 19 10:23 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 10:23 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 10:23 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 19 10:23 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 10:23 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_xxozg07g:\r\n",
+ "total 4240\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9172 Aug 30 12:14 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 30 12:14 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 12416 Aug 30 12:14 input.npy\r\n",
+ "-rw-r--r-- 1 root root 208 Aug 30 12:51 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 30 12:15 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 30 12:14 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 30 12:14 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 30 12:51 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_y5v0yh_k:\r\n",
+ "total 4228\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8827 Aug 15 00:25 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 15 00:25 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 15 00:25 input.npy\r\n",
+ "-rw-r--r-- 1 root root 206 Aug 15 00:34 nw_metrics.txt\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 15 00:26 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 15 00:25 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Aug 15 00:25 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 15 00:34 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_ybgtgj39:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9147 Aug 30 09:56 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 30 09:56 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 144 Aug 30 09:56 input.npy\r\n",
+ "-rw-r--r-- 1 root root 96 Aug 30 09:56 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 30 09:56 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246209 Aug 30 09:56 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 30 09:56 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_yqc16_8w:\r\n",
+ "total 20\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8820 Aug 18 12:40 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 18 12:40 finn\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 18 12:40 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_yt2dpnht:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9217 Aug 16 13:40 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 16 13:40 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 16 13:40 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 16 13:41 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 16 13:40 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246651 Aug 16 13:40 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 16 13:41 sds_trace_data.dat\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_z5zzp4mm:\r\n",
+ "total 4212\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9409 Sep 4 13:07 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 13:07 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 13:07 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 13:07 resizer.hwh\r\n",
+ "\r\n",
+ "/home/xilinx/finn_dev_maltanar/pynq_deployment_zn65nxuo:\r\n",
+ "total 4224\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 8825 Aug 19 00:58 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Aug 19 00:58 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 3264 Aug 19 00:58 input.npy\r\n",
+ "-rw-r--r-- 1 root root 120 Aug 19 00:59 output.npy\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Aug 19 00:58 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246651 Aug 19 00:58 resizer.hwh\r\n",
+ "-rw-r--r-- 1 root root 32 Aug 19 00:59 sds_trace_data.dat\r\n"
]
}
],
@@ -609,30 +1318,18 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "<matplotlib.image.AxesImage at 0x7f0c2b2c6908>"
+ "<matplotlib.image.AxesImage at 0x7fc315a36198>"
]
},
- "execution_count": 19,
+ "execution_count": 24,
"metadata": {},
"output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
}
],
"source": [
@@ -655,7 +1352,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
@@ -676,7 +1373,7 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
@@ -698,7 +1395,7 @@
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": 27,
"metadata": {},
"outputs": [
{
@@ -707,13 +1404,13 @@
"<BarContainer object of 10 artists>"
]
},
- "execution_count": 28,
+ "execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1440x216 with 1 Axes>"
]
diff --git a/notebooks/end2end_example/finn-design-flow-example.svg b/notebooks/end2end_example/finn-design-flow-example.svg
index 04f568c1f..fa36be96c 100755
--- a/notebooks/end2end_example/finn-design-flow-example.svg
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diff --git a/notebooks/end2end_example/tfc_end2end_example.ipynb b/notebooks/end2end_example/tfc_end2end_example.ipynb
index 6aebd9bd1..1db1dd84c 100644
--- a/notebooks/end2end_example/tfc_end2end_example.ipynb
+++ b/notebooks/end2end_example/tfc_end2end_example.ipynb
@@ -132,7 +132,7 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f7cc4290940>"
+ "<IPython.lib.display.IFrame at 0x7f98457e4048>"
]
},
"execution_count": 3,
@@ -293,7 +293,7 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f7c6c567f28>"
+ "<IPython.lib.display.IFrame at 0x7f97d7ff7cf8>"
]
},
"execution_count": 6,
@@ -402,7 +402,7 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f7c6c0bf898>"
+ "<IPython.lib.display.IFrame at 0x7f97d46a65f8>"
]
},
"execution_count": 8,
@@ -456,7 +456,7 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7f7c6c0e5c18>"
+ "<IPython.lib.display.IFrame at 0x7f97d46ad240>"
]
},
"execution_count": 9,
@@ -532,7 +532,7 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7fe1346f1080>"
+ "<IPython.lib.display.IFrame at 0x7f97d46a6668>"
]
},
"execution_count": 10,
@@ -592,7 +592,7 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7fe1ad0b6e48>"
+ "<IPython.lib.display.IFrame at 0x7f9872793940>"
]
},
"execution_count": 11,
@@ -627,7 +627,7 @@
"text": [
"\n",
"Stopping http://0.0.0.0:8081\n",
- "Serving '/tmp/finn_dev_jakobap/dataflow_partition_pbrjefjg/df_model.onnx' at http://0.0.0.0:8081\n"
+ "Serving '/tmp/finn_dev_maltanar/dataflow_partition0_cuza0or8/df_model.onnx' at http://0.0.0.0:8081\n"
]
},
{
@@ -644,7 +644,7 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7fe1346f3550>"
+ "<IPython.lib.display.IFrame at 0x7f987278b9e8>"
]
},
"execution_count": 12,
@@ -679,7 +679,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "### Folding and Datawidth Converter, FIFO and TLastMarker Insertion <a id='folding'></a>\n",
+ "### Folding: Adjusting the Parallelism <a id='folding'></a>\n",
"\n",
"*Folding* in FINN describes how much a layer is time-multiplexed in terms of execution resources. There are several *folding factors* for each layer, controlled by the PE (parallelization over outputs) and SIMD (parallelization over inputs) parameters as described by the original [FINN paper](https://arxiv.org/pdf/1612.07119). The higher the PE and SIMD values are set, the faster the generated accelerator will run, and the more FPGA resources it will consume. \n",
"\n",
@@ -717,6 +717,7 @@
" 'inputDataType': ('s', True, ''),\n",
" 'weightDataType': ('s', True, ''),\n",
" 'outputDataType': ('s', True, ''),\n",
+ " 'accDataType': ('s', False, 'INT32'),\n",
" 'binaryXnorMode': ('i', False, 0),\n",
" 'noActivation': ('i', False, 0),\n",
" 'numInputVectors': ('ints', False, [1]),\n",
@@ -731,11 +732,13 @@
" 'ip_vlnv': ('s', False, ''),\n",
" 'exec_mode': ('s', False, ''),\n",
" 'cycles_rtlsim': ('i', False, 0),\n",
+ " 'cycles_estimate': ('i', False, 0),\n",
" 'rtlsim_trace': ('s', False, ''),\n",
" 'res_estimate': ('s', False, ''),\n",
" 'res_hls': ('s', False, ''),\n",
" 'res_synth': ('s', False, ''),\n",
" 'rtlsim_so': ('s', False, ''),\n",
+ " 'partition_id': ('i', False, 0),\n",
" 'inFIFODepth': ('i', False, 2),\n",
" 'outFIFODepth': ('i', False, 2)}"
]
@@ -797,36 +800,14 @@
"metadata": {},
"source": [
"Besides PE and SIMD three other node attributes are set. `ram_style` specifies how the weights are to be stored (BRAM, LUTRAM, and so on). It can be selected explicitly or with the option `auto` you can let Vivado decide.\n",
- "`inFIFODepth` and `outFIFODepth` specifies the FIFO depths that is needed by the node from the surrounding FIFOs. These attributes are used in the transformation 'InsertFIFO' to insert the appropriate FIFOs between the nodes.\n",
+ "`inFIFODepth` and `outFIFODepth` specifies the FIFO depths that is needed by the node from the surrounding FIFOs. These attributes are used in the transformation 'InsertFIFO' to insert the appropriate FIFOs between the nodes, which will be automatically called as part of the hardware build process.\n",
"\n",
- "But before FIFOs can be added, it must be determined whether datawidth converters (DWC) are required and they must be inserted correctly. Because by setting the folding, the folded output shape of one node may not match the folded input shape of the next node. \n",
- "\n",
- "In the following, first DWCs and then FIFOs are inserted using the corresponding transformations in FINN."
+ "In previous versions of FINN we had to call transformations to insert data width converters, FIFOs and `TLastMarker` manually at this step. This is no longer needed, as all this is taken care of by the `ZynqBuild` or `VitisBuild` transformations."
]
},
{
"cell_type": "code",
"execution_count": 16,
- "metadata": {},
- "outputs": [],
- "source": [
- "from finn.transformation.fpgadataflow.insert_dwc import InsertDWC\n",
- "from finn.transformation.fpgadataflow.insert_fifo import InsertFIFO\n",
- "\n",
- "model = model.transform(InsertDWC())\n",
- "model = model.transform(InsertFIFO())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Finally, we will run the `InsertTLastMarker` transformation to get a `TLastMarker` node at the output of this graph, which is necessary to run the DMA engines correctly. Using netron we can observe that now the nodes contain the set folding, if necessary a DWC is inserted, inbetween the nodes are FIFOs inserted and the last node is the `TLastMarker` node we insert in the following."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
"metadata": {
"scrolled": true
},
@@ -854,17 +835,15 @@
" "
],
"text/plain": [
- "<IPython.lib.display.IFrame at 0x7fe135b84780>"
+ "<IPython.lib.display.IFrame at 0x7f97d464ca20>"
]
},
- "execution_count": 17,
+ "execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "from finn.transformation.fpgadataflow.insert_tlastmarker import InsertTLastMarker\n",
- "model = model.transform(InsertTLastMarker())\n",
"model.save(build_dir+\"/tfc_w1_a1_set_folding_factors.onnx\")\n",
"showInNetron(build_dir+\"/tfc_w1_a1_set_folding_factors.onnx\")"
]
@@ -880,10 +859,9 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "## 3. Vivado HLS and IPI <a id='vivado'></a>\n",
- "* [Generating HLS Code](#hls_per_layer)\n",
- "* [Synthesizing HLS to IP Blocks](#hls_synth)\n",
- "* [IP Stitching](#ip_stitching)\n",
+ "## 3. Hardware Build <a id='vivado'></a>\n",
+ "\n",
+ "We're finally ready to start generating hardware from our network. Depending on whether you want to target a Zynq or Alveo platform, FINN offers two transformations to build the accelerator, integrate into an appropriate shell and build a bitfile. These are `ZynqBuild` and `VitisBuild` for Zynq and Alveo, respectively. In this notebook we'll demonstrate the `ZynqBuild` as these boards are more common and it's much faster to complete bitfile generation for the smaller FPGAs found on them.\n",
"\n",
"As we will be dealing with FPGA synthesis tools in these tasks, we'll define two helper variables that describe the Xilinx FPGA part name and the PYNQ board name that we are targeting."
]
@@ -897,7 +875,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "dict_keys(['Ultra96', 'Pynq-Z1', 'Pynq-Z2', 'ZCU104'])\n"
+ "dict_keys(['Ultra96', 'Pynq-Z1', 'Pynq-Z2', 'ZCU102', 'ZCU104'])\n"
]
}
],
@@ -923,342 +901,53 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "### Generating HLS Code <a id='hls_per_layer'></a>\n",
- "This section deals with the generation of an IP block from the different layers. These can then be stitched to a block design that corresponds to the complete model. The single conversion into IP blocks allows a good transparency and we can check the functionality of each IP block and compare it with the behaviour of the corresponding ONNX node. "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Two transformations are required to generate HLS IP blocks for each layer: \n",
- "* `PrepareIP` which generates the HLS C++ code for the node and a tcl-script which starts the HLS synthesis and exports the design as IP. \n",
- "* `HLSSynthIP` which passes the tcl-script to Vivado HLS and thus performs the actual IP generation. \n",
- "\n",
- "We start off by giving unique node names using the basic transformation `GiveUniqueNodeNames`, and then proceed with the HLS C++ code generation with `PrepareIP`."
+ "In previous versions of FINN, we had to manually go through several steps to generate HLS code, stitch IP, create a PYNQ project and run synthesis. All these steps are now performed by the `ZynqBuild` transform (or the `VitisBuild` transform for Alveo). **As this involves calling HLS synthesis and Vivado synthesis, this transformation will run for some time (up to half an hour depending on your PC).**"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
- "outputs": [],
- "source": [
- "model = ModelWrapper(build_dir+\"/tfc_w1_a1_set_folding_factors.onnx\")\n",
- "model = model.transform(GiveUniqueNodeNames())\n",
- "\n",
- "from finn.transformation.fpgadataflow.prepare_ip import PrepareIP\n",
- "model = model.transform(PrepareIP(fpga_part, target_clk_ns))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Synthesizing HLS to IP Blocks <a id='hls_synth'></a>\n",
- "\n",
- "Now that we have generated the HLS code for each layer, we can call the `HLSSynthIP` transformation to convert the generated HLS into Vivado IP blocks. **As this involves calling HLS synthesis, this transformation will run for some time (several minutes).**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {},
- "outputs": [],
- "source": [
- "from finn.transformation.fpgadataflow.hlssynth_ip import HLSSynthIP\n",
- "\n",
- "model = model.transform(HLSSynthIP())\n",
- "model.save(build_dir+\"/tfc_w1_a1_ipgen.onnx\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Each `StreamingFCLayer_Batch` node now has new attributes which can be examined more closely with netron."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\n",
- "Stopping http://0.0.0.0:8081\n",
- "Serving '/workspace/finn/tfc_w1_a1_ipgen.onnx' at http://0.0.0.0:8081\n"
- ]
- },
- {
- "data": {
- "text/html": [
- "\n",
- " <iframe\n",
- " width=\"100%\"\n",
- " height=\"400\"\n",
- " src=\"http://0.0.0.0:8081/\"\n",
- " frameborder=\"0\"\n",
- " allowfullscreen\n",
- " ></iframe>\n",
- " "
- ],
- "text/plain": [
- "<IPython.lib.display.IFrame at 0x7fe1346f7588>"
- ]
- },
- "execution_count": 22,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "showInNetron(build_dir+\"/tfc_w1_a1_ipgen.onnx\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "There are two additional attributes: \n",
- "* `code_gen_dir_ipgen` which contains the directory path where all the files generated by the ipgen transformations are stored\n",
- "* `ipgen_path` which contains the path to the project directory in which the generated IP block is stored\n",
- "\n",
- "We can further investigate which files are produced by taking a look in this directory. For example for the first StreamingFCLayer_Batch node."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "StreamingFCLayer_Batch_0_memstream.v thresh.h\r\n",
- "hls_syn_StreamingFCLayer_Batch_0.tcl top_StreamingFCLayer_Batch_0.cpp\r\n",
- "ipgen.sh\t\t\t vivado_hls.log\r\n",
- "memblock_0.dat\t\t\t weights.npy\r\n",
- "project_StreamingFCLayer_Batch_0\r\n"
- ]
- }
- ],
- "source": [
- "fc0w = getCustomOp(model.graph.node[1])\n",
- "code_gen_dir = fc0w.get_nodeattr(\"code_gen_dir_ipgen\")\n",
- "!ls {code_gen_dir}"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Directory *project_StreamingFCLayer_Batch_0* contains the project created by Vivado HLS into which the IP Block is exported, along with other files generated by Vivado HLS. If we compare it to the above visualization of the network with netron, this is exactly the name of the folder stored in the node attribute `ipgen_path`. The .cpp code that is passed to Vivado HLS can be found in the file *top_StreamingFCLayer_Batch_0.cpp*. The file *thresh.h* belongs to that as well, it contains the value for the thresholds. The weights are stored as .npy file and as .dat file (*memblock_0.dat*). *vivado_hls.log* is the log file from Vivado HLS. Besides these files, the folder contains *ipgen.sh* and *hls_syn_StreamingFCLayer_Batch_0.tcl* and because we use the StreamingFCLayer in \"decoupled\" mode a verilog wrapper (*StreamingFCLayer_Batch_0_memstream.v*) is produced, for more details on \"decoupled\" and \"const\" mode please see on the [FINN readthedocs website](https://finn.readthedocs.io/) under Internals. \n",
- "\n",
- "In the following we take a closer look at the two generated scripts. We start with *ipgen.sh*."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "#!/bin/bash \r\n",
- "cd /tmp/finn_dev_jakobap/code_gen_ipgen_StreamingFCLayer_Batch_0_edb__5oc\r\n",
- "vivado_hls /tmp/finn_dev_jakobap/code_gen_ipgen_StreamingFCLayer_Batch_0_edb__5oc/hls_syn_StreamingFCLayer_Batch_0.tcl\r\n",
- "cd /workspace/finn\r\n"
- ]
- }
- ],
- "source": [
- "shell_script = code_gen_dir + \"/ipgen.sh\"\n",
- "!cat {shell_script}"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The script consists only of two framing `cd` commands and a command to pass the tcl script to *vivado_hls*. The directory has to be changed to create the files in the correct folder and will then be changed back to the original directory. \n",
- "\n",
- "Below is the tcl script which is passed to *vivado_hls*."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {},
"outputs": [
{
- "name": "stdout",
+ "name": "stderr",
"output_type": "stream",
"text": [
- "\r\n",
- "set config_proj_name project_StreamingFCLayer_Batch_0\r\n",
- "puts \"HLS project: $config_proj_name\"\r\n",
- "set config_hwsrcdir \"/tmp/finn_dev_jakobap/code_gen_ipgen_StreamingFCLayer_Batch_0_edb__5oc\"\r\n",
- "puts \"HW source dir: $config_hwsrcdir\"\r\n",
- "set config_proj_part \"xc7z020clg400-1\"\r\n",
- "\r\n",
- "set config_bnnlibdir \"/workspace/finn-hlslib\"\r\n",
- "\r\n",
- "set config_toplevelfxn \"StreamingFCLayer_Batch_0\"\r\n",
- "set config_clkperiod 10\r\n",
- "\r\n",
- "open_project $config_proj_name\r\n",
- "add_files $config_hwsrcdir/top_StreamingFCLayer_Batch_0.cpp -cflags \"-std=c++0x -I$config_bnnlibdir\"\r\n",
- "\r\n",
- "set_top $config_toplevelfxn\r\n",
- "open_solution sol1\r\n",
- "set_part $config_proj_part\r\n",
- "\r\n",
- "config_interface -m_axi_addr64\r\n",
- "config_rtl -auto_prefix\r\n",
- "\r\n",
- "\r\n",
- "create_clock -period $config_clkperiod -name default\r\n",
- "csynth_design\r\n",
- "export_design -format ip_catalog\r\n",
- "exit 0\r\n"
+ "/workspace/finn/src/finn/transformation/infer_data_layouts.py:107: UserWarning: Assuming 2D input is NC\n",
+ " warnings.warn(\"Assuming 2D input is NC\")\n"
]
}
],
"source": [
- "tcl_script = code_gen_dir + \"/hls_syn_StreamingFCLayer_Batch_0.tcl\"\n",
- "!cat {tcl_script}"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "In the first part of the script the project is configured. For example the FPGA part and the clock are set. Then the project is opened and the files are added. The toplevel function is set and after creating a clock, the design is first synthesized with `csynth` and then exported as an IP block.\n",
- "\n",
- "Now that all IP blocks are in place, they can be stitched together to create an IP design that matches the ONNX model. This is covered in the next section."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### IP Stitching <a id='ip_stitching'></a>\n",
- "\n",
- "We now have IP blocks for each of our layers, and will stitch them together into a larger IP that implements the whole network using the `CreateStitchedIP` transformation. Bear in mind that this transformation can only be applied on a graph that only contains HLS nodes that already have been through the `HLSSynthIP` transformation, which is the last step we performed. Prior to calling IP stitching, we'll also use the `ReplaceVerilogRelPaths` transformation to convert any relative `$readmemh` paths in the generated IP blocks to absolute ones, which prevents errors later on. **This step invokes Vivado and may take a few minutes to run.**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {},
- "outputs": [],
- "source": [
- "from finn.transformation.fpgadataflow.create_stitched_ip import CreateStitchedIP\n",
- "from finn.transformation.fpgadataflow.replace_verilog_relpaths import ReplaceVerilogRelPaths\n",
- "model = ModelWrapper(build_dir+\"/tfc_w1_a1_ipgen.onnx\")\n",
- "model = model.transform(ReplaceVerilogRelPaths())\n",
- "model = model.transform(CreateStitchedIP(fpga_part))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "If you examine the nodes themselves on the transformed model you won't see a difference, because the IP stitching adds model-level metadata to the graph. This can be accessed using the `.model.metadata_props`, the `get_metadata_prop` function in `ModelWrapper`, or by clicking on the global input/output tensors in Netron."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[key: \"vivado_stitch_proj\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl\"\n",
- ", key: \"vivado_stitch_vlnv\"\n",
- "value: \"xilinx_finn:finn:finn_design:1.0\"\n",
- ", key: \"wrapper_filename\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl/finn_vivado_stitch_proj.srcs/sources_1/bd/finn_design/hdl/finn_design_wrapper.v\"\n",
- "]"
- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "model.model.metadata_props"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl'"
- ]
- },
- "execution_count": 28,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "model.get_metadata_prop(\"vivado_stitch_proj\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "If you navigate to the folder above (remember the /tmp/finn_xxx folder is mounted on the host as well as inside Docker) you can open the Vivado project (.xpr) file there using Vivado, and view the following stitched IP block design:"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- ""
+ "from finn.transformation.fpgadataflow.make_zynq_proj import ZynqBuild\n",
+ "model = ModelWrapper(build_dir+\"/tfc_w1_a1_set_folding_factors.onnx\")\n",
+ "model = model.transform(ZynqBuild(platform = pynq_board, period_ns = target_clk_ns))"
]
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
- "model.save(build_dir+\"/tfc_w1_a1_ipstitch.onnx\")"
+ "model.save(build_dir + \"/tfc_w1_a1_post_synthesis.onnx\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "At this point, one could take the generated stitched IP and integrate it into your own project using Vivado IP Integrator if desired. Here, we will continue the tutorial by assuming that we want to do a stand-alone deployment for this accelerator for a PYNQ board."
+ "### Examining the generated outputs <a id='gen_outputs'></a>\n",
+ "\n",
+ "TODO"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## 4. PYNQ hardware generation and deployment <a id='hw_test'></a>\n",
+ "## 4. PYNQ deployment <a id='hw_test'></a>\n",
"\n",
- "* [Inserting the IP into a PYNQ Overlay Shell](#pynq_shell)\n",
- "* [Synthesis, Place and Route](#synth_pl_ro)\n",
- "* [Driver Generation](#driver_gen)\n",
"* [Deployment and Remote Execution](#deploy)\n",
"* [Throughput Test on PYNQ Board](#throughput)\n",
"\n",
@@ -1266,360 +955,6 @@
"We are almost done preparing our hardware design. We'll now put it in a form suitable for use as a PYNQ overlay, synthesize and deploy it."
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Inserting the IP into a PYNQ Overlay Shell <a id='pynq_shell'></a>\n",
- "\n",
- "To deploy our accelerator on a PYNQ platform, it needs to be put inside an appropriate *shell* that bridges it with the interfaces that the underlying system exposes. FINN makes it easy to create a PYNQ-compatible overlay by inserting the stitched IP into an appropriate PYNQ shell with the `MakePYNQProject` transformation, and view the created PYNQ shell project directory using the `metadata_props`. **This invokes Vivado and may take a few minutes to run.**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[key: \"vivado_stitch_proj\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl\"\n",
- ", key: \"vivado_stitch_vlnv\"\n",
- "value: \"xilinx_finn:finn:finn_design:1.0\"\n",
- ", key: \"wrapper_filename\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl/finn_vivado_stitch_proj.srcs/sources_1/bd/finn_design/hdl/finn_design_wrapper.v\"\n",
- ", key: \"vivado_pynq_proj\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs\"\n",
- ", key: \"vivado_synth_rpt\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs/synth_report.xml\"\n",
- "]"
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "from finn.transformation.fpgadataflow.make_pynq_proj import MakePYNQProject\n",
- "model = ModelWrapper(build_dir+\"/tfc_w1_a1_ipstitch.onnx\")\n",
- "model = model.transform(MakePYNQProject(pynq_board))\n",
- "model.model.metadata_props"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "ip_config.tcl\t resizer.cache\tresizer.ip_user_files resizer.xpr\r\n",
- "make_project.sh resizer.hw\tresizer.srcs\t synth_project.sh\r\n"
- ]
- }
- ],
- "source": [
- "! ls {model.get_metadata_prop(\"vivado_pynq_proj\")}"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "If we open the created Vivado project (.xpr) under the `vivado_pynq_proj` directory above, we can see the system-level block design as below, with the FINN-generated part of the design highlighted. Various other components, such as the DMA engine and data width converters, have also been instantiated.\n",
- ""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {},
- "outputs": [],
- "source": [
- "model.save(build_dir + \"/tfc_w1_a1_pynq_project.onnx\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Synthesis, Place and Route <a id='synth_pl_ro'></a>"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We are now ready for the final hardware generation step, which is synthesis, place and route to generate an FPGA bitfile. This can be done by either running the `synth_project.sh` script in the generated Vivado PYNQ project directory inside Docker, or by executing the `SynthPYNQProject` transformation. **This step involves launching Vivado for synthesis and may take a few hours.**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[key: \"vivado_stitch_proj\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl\"\n",
- ", key: \"vivado_stitch_vlnv\"\n",
- "value: \"xilinx_finn:finn:finn_design:1.0\"\n",
- ", key: \"wrapper_filename\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl/finn_vivado_stitch_proj.srcs/sources_1/bd/finn_design/hdl/finn_design_wrapper.v\"\n",
- ", key: \"vivado_pynq_proj\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs\"\n",
- ", key: \"vivado_synth_rpt\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs/synth_report.xml\"\n",
- ", key: \"bitfile\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs/resizer.bit\"\n",
- "]"
- ]
- },
- "execution_count": 33,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "from finn.transformation.fpgadataflow.synth_pynq_proj import SynthPYNQProject\n",
- "model = ModelWrapper(build_dir + \"/tfc_w1_a1_pynq_project.onnx\")\n",
- "model = model.transform(SynthPYNQProject())\n",
- "model.model.metadata_props"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 34,
- "metadata": {},
- "outputs": [],
- "source": [
- "model.save(build_dir + \"/tfc_w1_a1_post_synthesis.onnx\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Driver Generation <a id='driver_gen'></a>\n",
- "\n",
- "Now that we have synthesized a bitfile for our network, we will generate some Python code for PYNQ that will act as the driver for this bitfile, package everything into a deployment folder and copy that to our PYNQ board."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {},
- "outputs": [],
- "source": [
- "from finn.transformation.fpgadataflow.make_pynq_driver import MakePYNQDriver\n",
- "model = ModelWrapper(build_dir + \"/tfc_w1_a1_post_synthesis.onnx\")\n",
- "model = model.transform(MakePYNQDriver(platform=\"zynq\"))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The generated driver is placed in a folder that is indicated by the `pynq_driver_dir` top-level metadata. We can examine the generated PYNQ Python driver code as follows:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\r\n",
- "import argparse\r\n",
- "\r\n",
- "from pynq import Overlay\r\n",
- "import numpy as np\r\n",
- "from pynq import allocate\r\n",
- "import time\r\n",
- "from finn.util.data_packing import (\r\n",
- " finnpy_to_packed_bytearray,\r\n",
- " packed_bytearray_to_finnpy\r\n",
- ")\r\n",
- "from finn.core.datatype import DataType\r\n",
- "\r\n",
- "class FINNAccelDriver():\r\n",
- " def __init__(self, N, bitfile):\r\n",
- " \"\"\"Instantiate the FINN accelerator driver.\r\n",
- " Gets batchsize (N) as integer and path to bitfile as string.\"\"\"\r\n",
- " self.N = N\r\n",
- " # input FINN DataType\r\n",
- " self.idt = DataType.BINARY\r\n",
- " # output FINN DataType\r\n",
- " self.odt = DataType.UINT32\r\n",
- " # input and output shapes\r\n",
- " self.ishape_normal = (N, 784)\r\n",
- " self.oshape_normal = (N, 10)\r\n",
- " self.ishape_folded = (N, 16, 49)\r\n",
- " self.oshape_folded = (N, 1, 10)\r\n",
- " self.ishape_packed = (N, 16, 7) # datatype np.uint8\r\n",
- " self.oshape_packed = (N, 1, 40) # datatype np.uint8\r\n",
- " # load bitfile and set up accelerator\r\n",
- " self.ol = Overlay(bitfile)\r\n",
- " self.dma = self.ol.axi_dma_0\r\n",
- " self.ctrl_regs = self.ol.resize_accel_0\r\n",
- " # neuron folding factor of output = iterations per sample\r\n",
- " self.itersPerSample = self.oshape_packed[-2]\r\n",
- " # AXI lite register offset for number of iterations\r\n",
- " # used by TLastMarker to signal end of transmission for AXI CDMA\r\n",
- " self.REG_OFFSET_NUM_ITERS = 0x10\r\n",
- " # set up TLastMarker with correct num. samples\r\n",
- " self.ctrl_regs.write(self.REG_OFFSET_NUM_ITERS, self.N*self.itersPerSample)\r\n",
- "\r\n",
- " # allocate a PYNQ buffer for the packed input and buffer\r\n",
- " self.ibuf_packed_device = allocate(shape=self.ishape_packed, dtype=np.uint8)\r\n",
- " self.obuf_packed_device = allocate(shape=self.oshape_packed, dtype=np.uint8)\r\n",
- "\r\n",
- " def fold_input(self, ibuf_normal):\r\n",
- " \"\"\"Reshapes input in desired shape.\r\n",
- " Gets input data (ibuf_normal), checks if data is in expected normal shape.\r\n",
- " Returns folded input.\"\"\"\r\n",
- " # ensure that shape is as expected\r\n",
- " assert ibuf_normal.shape == self.ishape_normal\r\n",
- " # convert to folded form\r\n",
- " ibuf_folded = ibuf_normal.reshape(self.ishape_folded)\r\n",
- " return ibuf_folded\r\n",
- "\r\n",
- " def pack_input(self, ibuf_folded):\r\n",
- " \"\"\"Packs folded input and reverses both SIMD dim and endianness.\r\n",
- " Gets input data in folded shape and returns packed input data.\"\"\"\r\n",
- " ibuf_packed = finnpy_to_packed_bytearray(\r\n",
- " ibuf_folded, self.idt, reverse_endian=True, reverse_inner=True\r\n",
- " )\r\n",
- " return ibuf_packed\r\n",
- "\r\n",
- " def unpack_output(self, obuf_packed):\r\n",
- " \"\"\"Unpacks the packed output buffer from accelerator.\r\n",
- " Gets packed output and returns output data in folded shape.\"\"\"\r\n",
- " obuf_folded = packed_bytearray_to_finnpy(\r\n",
- " obuf_packed, self.odt, self.oshape_folded, reverse_endian=True, reverse_inner=True\r\n",
- " )\r\n",
- " return obuf_folded\r\n",
- "\r\n",
- " def unfold_output(self, obuf_folded):\r\n",
- " \"\"\"Unfolds output data to normal shape.\r\n",
- " Gets folded output data and returns output data in normal shape.\"\"\"\r\n",
- " obuf_normal = obuf_folded.reshape(self.oshape_normal)\r\n",
- " return obuf_normal\r\n",
- "\r\n",
- " def copy_input_data_to_device(self, data):\r\n",
- " \"\"\"Copies given input data to PYNQ buffer.\"\"\"\r\n",
- " np.copyto(self.ibuf_packed_device, data)\r\n",
- "\r\n",
- " def execute(self):\r\n",
- " \"\"\"Executes accelerator by setting up the DMA and\r\n",
- " waiting until all transfers complete. Uses only member variables and\r\n",
- " returns nothing.\"\"\"\r\n",
- " dma = self.dma\r\n",
- " dma.sendchannel.transfer(self.ibuf_packed_device)\r\n",
- " dma.recvchannel.transfer(self.obuf_packed_device)\r\n",
- " dma.sendchannel.wait()\r\n",
- " dma.recvchannel.wait()\r\n",
- "\r\n",
- "\r\n",
- "if __name__ == \"__main__\":\r\n",
- " parser = argparse.ArgumentParser(description='Set exec mode, batchsize N, bitfile name, inputfile name and outputfile name')\r\n",
- " parser.add_argument('--exec_mode', help='Please select functional verification (\"execute\") or throughput test (\"throughput_test\")', default=\"execute\")\r\n",
- " parser.add_argument('--batchsize', help='number of samples for inference', type=int, default=1)\r\n",
- " parser.add_argument('--bitfile', help='name of bitfile (i.e. \"resizer.bit\")', default=\"resizer.bit\")\r\n",
- " parser.add_argument('--inputfile', help='name of input npy file (i.e. \"input.npy\")', default=\"input.npy\")\r\n",
- " parser.add_argument('--outputfile', help='name of output npy file (i.e. \"output.npy\")', default=\"output.npy\")\r\n",
- " # parse arguments\r\n",
- " args = parser.parse_args()\r\n",
- " exec_mode = args.exec_mode\r\n",
- " N = args.batchsize\r\n",
- " bitfile = args.bitfile\r\n",
- " inputfile = args.inputfile\r\n",
- " outputfile = args.outputfile\r\n",
- "\r\n",
- " # instantiate FINN accelerator driver and pass batchsize and bitfile\r\n",
- " finnDriver = FINNAccelDriver(N, bitfile)\r\n",
- "\r\n",
- " # for the remote execution the data from the input npy file has to be loaded,\r\n",
- " # packed and copied to the PYNQ buffer\r\n",
- " if exec_mode == \"execute\":\r\n",
- " # load desired input .npy file\r\n",
- " ibuf_normal = np.load(inputfile)\r\n",
- " ibuf_folded = finnDriver.fold_input(ibuf_normal)\r\n",
- " ibuf_packed = finnDriver.pack_input(ibuf_folded)\r\n",
- " finnDriver.copy_input_data_to_device(ibuf_packed)\r\n",
- " elif exec_mode != \"throughput_test\":\r\n",
- " raise Exception(\"Exec mode has to be set to remote_pynq or throughput_test\")\r\n",
- "\r\n",
- " # for the throughput test the runtime of the network has to be measured\r\n",
- " if exec_mode == \"throughput_test\":\r\n",
- " # measure runtime of network\r\n",
- " start = time.time()\r\n",
- " # dictionary for results of throughput test\r\n",
- " res={}\r\n",
- "\r\n",
- " # execute accelerator\r\n",
- " finnDriver.execute()\r\n",
- "\r\n",
- " # measure run time and fill dictionary with results of the throughput test\r\n",
- " if exec_mode == \"throughput_test\":\r\n",
- " end = time.time()\r\n",
- " runtime = end - start\r\n",
- " res[\"runtime[ms]\"] = runtime*1000\r\n",
- " res[\"throughput[images/s]\"] = N / runtime\r\n",
- " res[\"DRAM_in_bandwidth[Mb/s]\"] = np.prod(finnDriver.ishape_packed)*0.000001 / runtime\r\n",
- " res[\"DRAM_out_bandwidth[Mb/s]\"] = np.prod(finnDriver.oshape_packed)*0.000001 / runtime\r\n",
- " file = open(\"nw_metrics.txt\", \"w\")\r\n",
- " file.write(str(res))\r\n",
- " file.close()\r\n",
- "\r\n",
- " # if execution is selected unpack, unfold and save output to output npy file\r\n",
- " else:\r\n",
- " obuf_folded = finnDriver.unpack_output(finnDriver.obuf_packed_device)\r\n",
- " obuf_normal = finnDriver.unfold_output(obuf_folded)\r\n",
- " np.save(outputfile, obuf_normal)\r\n",
- "\r\n",
- "\r\n"
- ]
- }
- ],
- "source": [
- "driver_dir = model.get_metadata_prop(\"pynq_driver_dir\")\n",
- "! cat {driver_dir}/driver.py"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We can see that in the generated driver a class is implemented which implements the FINN accelerator. The constructor gets the batchsize (N) as integer and the bitfile as string. It also contains the expected input/output shapes, and takes care of the instantiation of the accelerator by loading the bitfile and setting up dma and buffer. Several member functions take care of the data folding and packing. The function `copy_input_data_to_device` copies the input data into the PYNQ buffer and `execute` sets up the dma channels and waits until the transfer is completed. This class is used in the main function. But first the arguments are parsed, which are passed to the script. The driver can be used in two modes: \"execute\" and \"throughput_test\". By default all arguments are set to \"execute\" mode. In this mode the batch size is 1, and the passed files are set to the names used by the FINN transformations.\n",
- "\n",
- "In the \"execute\" mode works as follows:\n",
- "1. the data is loaded from the \"inputfile\"\n",
- "2. the data is folded using `fold_input`\n",
- "3. the data is packed using `pack_input`\n",
- "4. the data is copied to the device using `copy_input_data_to_device`\n",
- "5. FINNAccelDriver is executed using `execute`\n",
- "6. the data is unpacked using `unpack_output`\n",
- "7. the data is unfolded using `unfold_output`\n",
- "8. the data is stored in the \"outputfile\"\n",
- "\n",
- "If \"throughput_test\" is selected as `exec_mode`, no actual data needs to be loaded. The batchsize N should be set to a high value (i.e. 1000) and a time measurement is implemented in python. An empty dictionary (`res`) is created and after running the accelerator with the measured runtime it is filled with the metrics and saved in a .txt file.\n",
- "\n",
- "You can build your own applications around the accelerator by modifying the driver, or use the remote execution capabilities that FINN provides just to check if it is working, which will be our next step."
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -1631,12 +966,12 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"from finn.transformation.fpgadataflow.make_deployment import DeployToPYNQ\n",
- "ip = \"192.168.3.1\"\n",
+ "ip = \"192.168.2.99\"\n",
"port = \"22\"\n",
"username = \"xilinx\"\n",
"password = \"xilinx\"\n",
@@ -1654,46 +989,44 @@
},
{
"cell_type": "code",
- "execution_count": 38,
+ "execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[key: \"vivado_stitch_proj\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl\"\n",
- ", key: \"vivado_stitch_vlnv\"\n",
- "value: \"xilinx_finn:finn:finn_design:1.0\"\n",
- ", key: \"wrapper_filename\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_stitch_proj_oa43bqzl/finn_vivado_stitch_proj.srcs/sources_1/bd/finn_design/hdl/finn_design_wrapper.v\"\n",
+ "[key: \"pynq_driver_dir\"\n",
+ "value: \"/tmp/finn_dev_maltanar/pynq_driver_f266zjp6\"\n",
", key: \"vivado_pynq_proj\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs\"\n",
- ", key: \"vivado_synth_rpt\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs/synth_report.xml\"\n",
+ "value: \"/tmp/finn_dev_maltanar/vivado_zynq_proj__qx46zlk\"\n",
", key: \"bitfile\"\n",
- "value: \"/tmp/finn_dev_jakobap/vivado_pynq_proj_ljn53hfs/resizer.bit\"\n",
- ", key: \"pynq_driver_dir\"\n",
- "value: \"/tmp/finn_dev_jakobap/pynq_driver_j_9suyqm\"\n",
+ "value: \"/tmp/finn_dev_maltanar/vivado_zynq_proj__qx46zlk/resizer.bit\"\n",
+ ", key: \"hw_handoff\"\n",
+ "value: \"/tmp/finn_dev_maltanar/vivado_zynq_proj__qx46zlk/resizer.hwh\"\n",
+ ", key: \"vivado_synth_rpt\"\n",
+ "value: \"/tmp/finn_dev_maltanar/vivado_zynq_proj__qx46zlk/synth_report.xml\"\n",
+ ", key: \"platform\"\n",
+ "value: \"zynq-iodma\"\n",
", key: \"pynq_ip\"\n",
- "value: \"51.37.47.42\"\n",
+ "value: \"192.168.2.99\"\n",
", key: \"pynq_port\"\n",
- "value: \"23\"\n",
+ "value: \"22\"\n",
", key: \"pynq_username\"\n",
"value: \"xilinx\"\n",
", key: \"pynq_password\"\n",
- "value: \"x1l1nx_f!nn\"\n",
+ "value: \"xilinx\"\n",
", key: \"pynq_target_dir\"\n",
"value: \"/home/xilinx/finn_tfc_end2end_example\"\n",
", key: \"pynq_deployment_dir\"\n",
- "value: \"/tmp/finn_dev_jakobap/pynq_deployment_962qxwkv\"\n",
+ "value: \"/tmp/finn_dev_maltanar/pynq_deployment_624bd_nc\"\n",
", key: \"pynq_deploy_dir\"\n",
- "value: \"/tmp/finn_dev_jakobap/pynq_deployment_962qxwkv\"\n",
+ "value: \"/tmp/finn_dev_maltanar/pynq_deployment_624bd_nc\"\n",
", key: \"exec_mode\"\n",
"value: \"remote_pynq\"\n",
"]"
]
},
- "execution_count": 38,
+ "execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
@@ -1704,63 +1037,18 @@
},
{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "/home/xilinx/finn_tfc_end2end_example/pynq_deployment_26e8h5jo:\r\n",
- "total 4276\r\n",
- "-rw-r--r-- 1 xilinx xilinx 6363 May 7 10:35 driver.py\r\n",
- "drwxr-xr-x 4 xilinx xilinx 4096 May 7 10:35 finn\r\n",
- "-rw-r--r-- 1 xilinx xilinx 3264 May 7 10:55 input.npy\r\n",
- "-rw-r--r-- 1 root root 172 May 7 10:37 nw_metrics.txt\r\n",
- "-rw-r--r-- 1 root root 120 May 7 10:55 output.npy\r\n",
- "-rw-r--r-- 1 xilinx xilinx 4045675 May 7 10:35 resizer.bit\r\n",
- "-rw-r--r-- 1 xilinx xilinx 302015 May 7 10:35 resizer.hwh\r\n",
- "-rw-r--r-- 1 root root 32 May 7 10:55 sds_trace_data.dat\r\n",
- "\r\n",
- "/home/xilinx/finn_tfc_end2end_example/pynq_deployment_962qxwkv:\r\n",
- "total 4260\r\n",
- "-rw-r--r-- 1 xilinx xilinx 6363 May 7 17:44 driver.py\r\n",
- "drwxr-xr-x 4 xilinx xilinx 4096 May 7 17:44 finn\r\n",
- "-rw-r--r-- 1 xilinx xilinx 4045675 May 7 17:44 resizer.bit\r\n",
- "-rw-r--r-- 1 xilinx xilinx 302015 May 7 17:44 resizer.hwh\r\n",
- "\r\n",
- "/home/xilinx/finn_tfc_end2end_example/pynq_deployment_kvurnk0c:\r\n",
- "total 4300\r\n",
- "-rw-r--r-- 1 xilinx xilinx 3861 Apr 27 12:36 driver.py\r\n",
- "drwxr-xr-x 4 xilinx xilinx 4096 Apr 27 12:37 finn\r\n",
- "-rw-r--r-- 1 xilinx xilinx 3264 Apr 27 12:37 input.npy\r\n",
- "-rw-r--r-- 1 root root 78 Apr 27 12:38 nw_metrics.txt\r\n",
- "-rw-r--r-- 1 root root 120 Apr 27 12:37 output.npy\r\n",
- "-rw-r--r-- 1 xilinx xilinx 4045675 Apr 27 12:36 resizer.bit\r\n",
- "-rw-r--r-- 1 xilinx xilinx 329531 Apr 27 12:36 resizer.hwh\r\n",
- "-rw-r--r-- 1 root root 32 Apr 27 12:38 sds_trace_data.dat\r\n",
- "\r\n",
- "/home/xilinx/finn_tfc_end2end_example/pynq_deployment__tnbutz_:\r\n",
- "total 4276\r\n",
- "-rw-r--r-- 1 xilinx xilinx 6363 May 6 17:34 driver.py\r\n",
- "drwxr-xr-x 4 xilinx xilinx 4096 May 6 17:34 finn\r\n",
- "-rw-r--r-- 1 xilinx xilinx 3264 May 6 17:34 input.npy\r\n",
- "-rw-r--r-- 1 root root 173 May 6 17:35 nw_metrics.txt\r\n",
- "-rw-r--r-- 1 root root 120 May 6 17:34 output.npy\r\n",
- "-rw-r--r-- 1 xilinx xilinx 4045675 May 6 17:34 resizer.bit\r\n",
- "-rw-r--r-- 1 xilinx xilinx 302015 May 6 17:34 resizer.hwh\r\n",
- "-rw-r--r-- 1 root root 32 May 6 17:35 sds_trace_data.dat\r\n",
- "\r\n",
- "/home/xilinx/finn_tfc_end2end_example/pynq_deployment_w4aa1r9k:\r\n",
- "total 4276\r\n",
- "-rw-r--r-- 1 xilinx xilinx 6363 May 7 15:05 driver.py\r\n",
- "drwxr-xr-x 4 xilinx xilinx 4096 May 7 15:05 finn\r\n",
- "-rw-r--r-- 1 xilinx xilinx 3264 May 7 15:06 input.npy\r\n",
- "-rw-r--r-- 1 root root 172 May 7 15:11 nw_metrics.txt\r\n",
- "-rw-r--r-- 1 root root 120 May 7 15:06 output.npy\r\n",
- "-rw-r--r-- 1 xilinx xilinx 4045675 May 7 15:05 resizer.bit\r\n",
- "-rw-r--r-- 1 xilinx xilinx 302015 May 7 15:05 resizer.hwh\r\n",
- "-rw-r--r-- 1 root root 32 May 7 15:11 sds_trace_data.dat\r\n"
+ "total 4212\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 9391 Sep 4 10:37 driver.py\r\n",
+ "drwxr-xr-x 4 xilinx xilinx 4096 Sep 4 10:37 finn\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 4045671 Sep 4 10:37 resizer.bit\r\n",
+ "-rw-r--r-- 1 xilinx xilinx 246211 Sep 4 10:37 resizer.hwh\r\n"
]
}
],
@@ -1777,30 +1065,18 @@
},
{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "<matplotlib.image.AxesImage at 0x7fe11dda48d0>"
+ "<matplotlib.image.AxesImage at 0x7f9857a748d0>"
]
},
- "execution_count": 41,
+ "execution_count": 25,
"metadata": {},
"output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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1K3saP6Kwm9kZkl6U9Gt3/6dh6rMkvejuf5K4HsIO1KzliTA2uDzoo5I+HBr04o27034gaUPVQQKoz0jejV8g6XVJ6yWdXpv3p5JukDRXg0/jP5V0S/FmXnRdPLIDNav0NL5dCDtQP+azA5kj7EAmCDuQCcIOZIKwA5kg7EAmCDuQCcIOZIKwA5kg7EAmCDuQCcIOZIKwA5kg7EAmkgtOttkeSVuHfD+1uKwbdevYunVcEmNrVTvHdkFZoaPz2b9242Zr3X1eYwMIdOvYunVcEmNrVafGxtN4IBOEHchE02Ff0fDtR7p1bN06LomxtaojY2v0NTuAzmn6kR1AhxB2IBONhN3MrjSz/zWzj8zsribGUMbMPjWz9cU21I3uT1fsobfLzDYMuWyKmb1iZpuLz8PusdfQ2LpiG+9gm/FG77umtz/v+Gt2M+uRtEnSX0raJukdSTe4+8aODqSEmX0qaZ67N34ChpktlHRQ0qrTW2uZ2T9K2uvu9xX/UU5297/rkrEt1x+4jXdNYyvbZvyv1eB9187tz1vRxCP7fEkfufsWdz8u6WlJSxoYR9dz99ck7f3KxUskrSy+XqnBP5aOKxlbV3D3fnd/r/j6gKTT24w3et8F4+qIJsI+Q9Lvhny/Td2137tL+o2ZvWtmy5oezDCmDdlma4ekaU0OZhjJbbw76SvbjHfNfdfK9udV8Qbd1y1w9z+T9H1JPy6ernYlH3wN1k29059J+rYG9wDsl/RQk4MpthlfI+l2d98/tNbkfTfMuDpyvzUR9u2Szhvy/czisq7g7tuLz7skPavBlx3dZOfpHXSLz7saHs+X3H2nuw+4+ylJP1eD912xzfgaSb9w92eKixu/74YbV6futybC/o6k2Wb2LTM7U9IPJT3fwDi+xszGF2+cyMzGS7pC3bcV9fOSbiq+vknSrxocy+/plm28y7YZV8P3XePbn7t7xz8kXaXBd+Q/lvT3TYyhZFwXSvrv4uODpscm6SkNPq07ocH3Nn4k6WxJr0raLOk/JE3porH9mwa39n5fg8Ga3tDYFmjwKfr7ktYVH1c1fd8F4+rI/cbpskAmeIMOyARhBzJB2IFMEHYgE4QdyARhBzJB2IFM/B+tIjCppYWKvAAAAABJRU5ErkJggg==\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
}
],
"source": [
@@ -1822,7 +1098,7 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
@@ -1842,7 +1118,7 @@
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
@@ -1864,7 +1140,7 @@
},
{
"cell_type": "code",
- "execution_count": 44,
+ "execution_count": 28,
"metadata": {},
"outputs": [
{
@@ -1873,13 +1149,13 @@
"<BarContainer object of 10 artists>"
]
},
- "execution_count": 44,
+ "execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
@@ -1920,7 +1196,7 @@
},
{
"cell_type": "code",
- "execution_count": 45,
+ "execution_count": 31,
"metadata": {},
"outputs": [
{
@@ -1928,10 +1204,12 @@
"output_type": "stream",
"text": [
"Network metrics:\n",
- "runtime[ms]: 1.4772415161132812\n",
- "throughput[images/s]: 676937.378954164\n",
- "DRAM_in_bandwidth[Mb/s]: 75.81698644286635\n",
- "DRAM_out_bandwidth[Mb/s]: 27.07749515816656\n"
+ "runtime[ms]: 7.485151290893555\n",
+ "throughput[images/s]: 1335978.3405000796\n",
+ "DRAM_in_bandwidth[Mb/s]: 130.9258773690078\n",
+ "DRAM_out_bandwidth[Mb/s]: 13.359783405000796\n",
+ "fclk[mhz]: 100.0\n",
+ "N: 10000\n"
]
}
],
@@ -1939,7 +1217,7 @@
"from finn.core.throughput_test import throughput_test_remote\n",
"\n",
"child_model = ModelWrapper(getCustomOp(sdp_node).get_nodeattr(\"model\"))\n",
- "res = throughput_test_remote(child_model)\n",
+ "res = throughput_test_remote(child_model, 10000)\n",
"print(\"Network metrics:\")\n",
"for key in res:\n",
" print(str(key) + \": \" + str(res[key]))"
@@ -1954,14 +1232,14 @@
},
{
"cell_type": "code",
- "execution_count": 46,
+ "execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "We reach approximately 43% of the ideal performance.\n"
+ "We reach approximately 86% of the ideal performance.\n"
]
}
],
@@ -1981,8 +1259,15 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "The measured values were recorded with a batch size of 1000 and at a frequency of 100 MHz. We will be improving the efficiency of the generated accelerator examples in the coming FINN releases."
+ "The measured values were recorded with a batch size of 10000 and at a frequency of 100 MHz. We will be improving the efficiency of the generated accelerator examples in the coming FINN releases."
]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {
--
GitLab