diff --git a/src/finn/core/throughput_test.py b/src/finn/core/throughput_test.py
index c82d540e29fc59b92a22bf011e823a9f8c076843..39e71efa8c5ca3cef786b35a45b89d9231d1115d 100644
--- a/src/finn/core/throughput_test.py
+++ b/src/finn/core/throughput_test.py
@@ -30,7 +30,7 @@ import os
import subprocess
-def throughput_test(model):
+def throughput_test(model, batchsize=1000):
"""Runs the throughput test for the given model remotely on the pynq board.
The metadata properties related to the pynq board have to be set.
Returns a dictionary with results of the throughput test"""
@@ -47,7 +47,8 @@ def throughput_test(model):
cmd = (
"sshpass -p {} ssh {}@{} -p {} "
'"cd {}/{}; echo "{}" | '
- 'sudo -S python3.6 driver.py --exec_mode="throughput_test" --batchsize=1000"'
+ 'sudo -S python3.6 driver.py --exec_mode="throughput_test" --batchsize=%d"'
+ % batchsize
).format(
pynq_password,
pynq_username,
diff --git a/src/finn/transformation/fpgadataflow/make_pynq_driver.py b/src/finn/transformation/fpgadataflow/make_pynq_driver.py
index 049ede5064d252bd6391184c4227e5367a8c1e2b..18d3db18da089a5dda4dbb6d97180dd4a20613b5 100644
--- a/src/finn/transformation/fpgadataflow/make_pynq_driver.py
+++ b/src/finn/transformation/fpgadataflow/make_pynq_driver.py
@@ -107,6 +107,13 @@ class MakePYNQDriver(Transformation):
driver = driver.replace("$OUTPUT_SHAPE_FOLDED$", mss(o_tensor_shape_folded))
driver = driver.replace("$OUTPUT_SHAPE_PACKED$", mss(o_tensor_shape_packed))
+ # clock settings for driver
+ clk_ns = float(model.get_metadata_prop("clk_ns"))
+ fclk_mhz = 1 / (clk_ns * 0.001)
+ # TODO change according to PYNQ board?
+ driver = driver.replace("$CLK_NAME$", "fclk0_mhz")
+ driver = driver.replace("$CLOCK_FREQ_MHZ$", str(fclk_mhz))
+
with open(driver_py, "w") as f:
f.write(driver)
# copy all the dependencies into the driver folder
diff --git a/src/finn/transformation/fpgadataflow/templates.py b/src/finn/transformation/fpgadataflow/templates.py
index 55ecb57decd2ac4fa08331b5ebbcb7fd2f0cd5c6..7ad555ef7fd1f1a8708ced605020f67b5d04985b 100644
--- a/src/finn/transformation/fpgadataflow/templates.py
+++ b/src/finn/transformation/fpgadataflow/templates.py
@@ -101,6 +101,7 @@ from finn.util.data_packing import (
packed_bytearray_to_finnpy
)
from finn.core.datatype import DataType
+from pynq.ps import Clocks
class FINNAccelDriver():
def __init__(self, N, bitfile):
@@ -118,8 +119,12 @@ class FINNAccelDriver():
self.oshape_folded = $OUTPUT_SHAPE_FOLDED$
self.ishape_packed = $INPUT_SHAPE_PACKED$ # datatype np.uint8
self.oshape_packed = $OUTPUT_SHAPE_PACKED$ # datatype np.uint8
+ # clock frequency
+ self.fclk_mhz = $CLOCK_FREQ_MHZ$
# load bitfile and set up accelerator
self.ol = Overlay(bitfile)
+ # set the clock frequency as specified by user during transformations
+ Clocks.$CLK_NAME$ = self.fclk_mhz
self.dma = self.ol.axi_dma_0
self.ctrl_regs = self.ol.resize_accel_0
# neuron folding factor of output = iterations per sample
@@ -228,6 +233,8 @@ if __name__ == "__main__":
res["throughput[images/s]"] = N / runtime
res["DRAM_in_bandwidth[Mb/s]"] = np.prod(finnDriver.ishape_packed)*0.000001 / runtime
res["DRAM_out_bandwidth[Mb/s]"] = np.prod(finnDriver.oshape_packed)*0.000001 / runtime
+ res["fclk[mhz]"] = Clocks.fclk0_mhz
+ res["N"] = N
file = open("nw_metrics.txt", "w")
file.write(str(res))
file.close()
diff --git a/tests/end2end/test_end2end_tfc_w1a1_throughput_test.py b/tests/end2end/test_end2end_tfc_w1a1.py
similarity index 98%
rename from tests/end2end/test_end2end_tfc_w1a1_throughput_test.py
rename to tests/end2end/test_end2end_tfc_w1a1.py
index 1ba149687bb80a0f977115bd380a09f70eef23f1..15c1c41b006c6f87d79a0e7eb6a4458838de5fd2 100644
--- a/tests/end2end/test_end2end_tfc_w1a1_throughput_test.py
+++ b/tests/end2end/test_end2end_tfc_w1a1.py
@@ -41,7 +41,6 @@ import onnx.numpy_helper as nph
import finn.transformation.fpgadataflow.convert_to_hls_layers as to_hls
import finn.transformation.streamline.absorb as absorb
from finn.core.onnx_exec import execute_onnx
-from finn.core.throughput_test import throughput_test
from finn.custom_op.registry import getCustomOp
from finn.transformation.bipolar_to_xnor import ConvertBipolarMatMulToXnorPopcount
from finn.transformation.fold_constants import FoldConstants
@@ -332,9 +331,6 @@ def test_end2end_tfc_w1a1_run_on_pynq():
ret = execute_onnx(parent_model, {iname: x}, True)
y = ret[oname]
assert np.isclose(y, y_golden).all()
- child_model = load_test_checkpoint_or_skip(sdp_node.get_nodeattr("model"))
- res = throughput_test(child_model)
- assert res is not None
except KeyError:
pytest.skip("PYNQ board IP address not specified")
diff --git a/tests/pynq/test_pynq_performance_end2end.py b/tests/pynq/test_pynq_performance_end2end.py
new file mode 100644
index 0000000000000000000000000000000000000000..c7be7ae33ef296ce673a4f11948d4a9998d67bed
--- /dev/null
+++ b/tests/pynq/test_pynq_performance_end2end.py
@@ -0,0 +1,57 @@
+import os
+
+import pytest
+import numpy as np
+from scipy.stats import linregress
+import warnings
+from finn.util.test import load_test_checkpoint_or_skip
+from finn.core.throughput_test import throughput_test
+
+build_dir = "/tmp/" + os.environ["FINN_INST_NAME"]
+
+
+@pytest.mark.parametrize("end2end_example", ["tfc_w1a1", "cnv_w1a1"])
+def test_pynq_performance_end2end(end2end_example):
+ model = load_test_checkpoint_or_skip(
+ build_dir + "/end2end_%s_pynq_deploy.onnx" % end2end_example
+ )
+ try:
+ ip = os.environ["PYNQ_IP"] # NOQA
+ board = os.environ["PYNQ_BOARD"] # NOQA
+ if ip == "" or board == "":
+ pytest.skip("PYNQ board or IP address not specified")
+ ret = dict()
+ bsize_range = [1, 10, 100, 1000, 10000]
+ for bsize in bsize_range:
+ res = throughput_test(model, bsize)
+ assert res is not None
+ ret[bsize] = res
+
+ y = [ret[key]["runtime[ms]"] for key in bsize_range]
+ lrret = linregress(bsize_range, y)
+ ret_str = ""
+ ret_str += "\n" + "%s Throughput Test Results" % end2end_example
+ ret_str += "\n" + "-----------------------------"
+ ret_str += "\n" + "From linear regression:"
+ ret_str += "\n" + "Invocation overhead: %f ms" % lrret.intercept
+ ret_str += "\n" + "Time per sample: %f ms" % lrret.slope
+ ret_str += "\n" + "Raw data:"
+
+ ret_str += "\n" + "{:<8} {:<16} {:<16} {:<16} {:<16} {:<16}".format(
+ "N", "runtime[ms]", "fclk[mhz]", "fps", "DRAM rd[Mb/s]", "DRAM wr[Mb/s]"
+ )
+ for k in bsize_range:
+ v = ret[k]
+ ret_str += "\n" + "{:<8} {:<16} {:<16} {:<16} {:<16} {:<16}".format(
+ k,
+ np.round(v["runtime[ms]"], 4),
+ v["fclk[mhz]"],
+ np.round(v["throughput[images/s]"], 2),
+ np.round(v["DRAM_in_bandwidth[Mb/s]"], 2),
+ np.round(v["DRAM_out_bandwidth[Mb/s]"], 2),
+ )
+ ret_str += "\n" + "-----------------------------"
+ warnings.warn(ret_str)
+
+ except KeyError:
+ pytest.skip("PYNQ board or IP address not specified")
diff --git a/tests/pynq/test_pynq_performance_fifo.py b/tests/pynq/test_pynq_performance_fifo.py
new file mode 100644
index 0000000000000000000000000000000000000000..7aaff9f6ed2af9d05bb4f3a805628ced9792dc35
--- /dev/null
+++ b/tests/pynq/test_pynq_performance_fifo.py
@@ -0,0 +1,120 @@
+import os
+
+import pytest
+
+import numpy as np
+from onnx import TensorProto, helper
+
+from finn.core.datatype import DataType
+from finn.core.modelwrapper import ModelWrapper
+from finn.transformation.fpgadataflow.prepare_ip import PrepareIP
+from finn.transformation.fpgadataflow.create_stitched_ip import CreateStitchedIP
+from finn.transformation.fpgadataflow.hlssynth_ip import HLSSynthIP
+from finn.transformation.fpgadataflow.insert_tlastmarker import InsertTLastMarker
+from finn.transformation.fpgadataflow.make_deployment import DeployToPYNQ
+from finn.transformation.fpgadataflow.make_pynq_driver import MakePYNQDriver
+from finn.transformation.fpgadataflow.make_pynq_proj import MakePYNQProject
+from finn.transformation.fpgadataflow.synth_pynq_proj import SynthPYNQProject
+import finn.transformation.fpgadataflow.replace_verilog_relpaths as rvp
+from finn.transformation.general import GiveUniqueNodeNames
+from finn.util.basic import pynq_part_map
+from finn.core.throughput_test import throughput_test
+from scipy.stats import linregress
+import warnings
+
+
+def make_single_fifo_modelwrapper(Shape, Depth, fld_shape, finn_dtype):
+
+ inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, Shape)
+ outp = helper.make_tensor_value_info("outp", TensorProto.FLOAT, Shape)
+
+ FIFO_node = helper.make_node(
+ "StreamingFIFO",
+ ["inp"],
+ ["outp"],
+ domain="finn",
+ backend="fpgadataflow",
+ depth=Depth,
+ folded_shape=fld_shape,
+ dataType=str(finn_dtype.name),
+ )
+
+ graph = helper.make_graph(
+ nodes=[FIFO_node], name="fifo_graph", inputs=[inp], outputs=[outp]
+ )
+
+ model = helper.make_model(graph, producer_name="fifo-model")
+ model = ModelWrapper(model)
+
+ model.set_tensor_datatype("inp", finn_dtype)
+ model.set_tensor_datatype("outp", finn_dtype)
+
+ return model
+
+
+@pytest.mark.vivado
+@pytest.mark.slow
+def test_pynq_performance_fifo():
+ try:
+ ip = os.environ["PYNQ_IP"] # NOQA
+ board = os.environ["PYNQ_BOARD"] # NOQA
+ if ip == "" or board == "":
+ pytest.skip("PYNQ board or IP address not specified")
+ shape = (1, 128)
+ folded_shape = (1, 1, 128)
+ depth = 16
+ clk_ns = 10
+ dtype = DataType.BIPOLAR
+ fpga_part = pynq_part_map[board]
+ username = os.getenv("PYNQ_USERNAME", "xilinx")
+ password = os.getenv("PYNQ_PASSWORD", "xilinx")
+ port = os.getenv("PYNQ_PORT", 22)
+ target_dir = os.getenv("PYNQ_TARGET_DIR", "/home/xilinx/finn")
+
+ model = make_single_fifo_modelwrapper(shape, depth, folded_shape, dtype)
+ model = model.transform(InsertTLastMarker())
+ model = model.transform(GiveUniqueNodeNames())
+ model = model.transform(PrepareIP(fpga_part, clk_ns))
+ model = model.transform(HLSSynthIP())
+ model = model.transform(rvp.ReplaceVerilogRelPaths())
+ model = model.transform(CreateStitchedIP(fpga_part, clk_ns))
+ model = model.transform(MakePYNQProject(board))
+ model = model.transform(SynthPYNQProject())
+ model = model.transform(MakePYNQDriver())
+ model = model.transform(DeployToPYNQ(ip, port, username, password, target_dir))
+
+ ret = dict()
+ bsize_range = [1, 10, 100, 1000, 10000, 100000]
+ for bsize in bsize_range:
+ res = throughput_test(model, bsize)
+ assert res is not None
+ ret[bsize] = res
+
+ y = [ret[key]["runtime[ms]"] for key in bsize_range]
+ lrret = linregress(bsize_range, y)
+ ret_str = ""
+ ret_str += "\n" + "FIFO Throughput Test Results"
+ ret_str += "\n" + "-----------------------------"
+ ret_str += "\n" + "From linear regression:"
+ ret_str += "\n" + "Invocation overhead: %f ms" % lrret.intercept
+ ret_str += "\n" + "Time per sample: %f ms" % lrret.slope
+ ret_str += "\n" + "Raw data:"
+
+ ret_str += "\n" + "{:<8} {:<16} {:<16} {:<16} {:<16} {:<16}".format(
+ "N", "runtime[ms]", "fclk[mhz]", "fps", "DRAM rd[Mb/s]", "DRAM wr[Mb/s]"
+ )
+ for k in bsize_range:
+ v = ret[k]
+ ret_str += "\n" + "{:<8} {:<16} {:<16} {:<16} {:<16} {:<16}".format(
+ k,
+ np.round(v["runtime[ms]"], 4),
+ v["fclk[mhz]"],
+ np.round(v["throughput[images/s]"], 2),
+ np.round(v["DRAM_in_bandwidth[Mb/s]"], 2),
+ np.round(v["DRAM_out_bandwidth[Mb/s]"], 2),
+ )
+ ret_str += "\n" + "-----------------------------"
+ warnings.warn(ret_str)
+
+ except KeyError:
+ pytest.skip("PYNQ board or IP address not specified")