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  1. Feb 21, 2021
    • Yaman Umuroglu's avatar
      [Docs] update tutorials · 7776475f
      Yaman Umuroglu authored
      7776475f
    • Yaman Umuroglu's avatar
      Custom op notebook (#283) · a65e08b0
      Yaman Umuroglu authored
      
      * [Notebook] start custom op nb
      
      * [Notebook] update custom_op notebook
      
      * [Notebook] update the custom op notebook to reflect new reg system
      
      * [Notebook] Added more descriptive text into the notebook (#278)
      
      * [Web] update publications
      
      * Build step: measure rtlsim performance (#262)
      
      * [Build] introduce step_measure_rtlsim_performance
      
      * [Docs] document the rtlsim performance step
      
      * [Docs] add comments on CPU/RAM/storage recommandations
      
      * [Build, Test] enable rtlsim perf as part of build test too
      
      * [Build] print where intermediate outputs are generated
      
      * [Docs] remove ghpages content, add note
      
      * [Docker] use -c continue for build_custom mode
      
      * [Docs] minor fixes
      
      * Driver data packing + improvements (#261)
      
      * [Driver] add driver_base.py as own template file + comments
      
      * [Driver] also move validation to won template + use in transform
      
      * [Driver] more comments
      
      * [Driver] suggested updates from PYNQ team + async mode exec_on_buffers
      
      * [Driver] allow smaller batchsize in execute_on_buffers
      
      * [Driver] optimize buffer alloc a bit
      
      * [Driver] wait condition fix
      
      * [Deps] update finn-base
      
      * [Deps] update finn-base
      
      * [Driver] enable fast_mode, expose more benchmarks
      
      * [Deps] update finn-base
      
      * [Driver] handle case with no rt weights
      
      * [Build] auto-exit build_custom if no errors
      
      * [Driver] get Alveo clock during test
      
      * Add report_utilization to stitched project tcl script (#243)
      
      * [Vitis] use -mode batch for report gen Vivado launch
      
      * Feature/cybersecurity notebook (#259)
      
      * Created cybersecurity notebook and downloaded data with wget
      
      * Reorganized the cybersecurity notebook
      
      * Read the entire dataset as a pytorch tensor and trained a simple MLP on the UNSW_NB15 dataset
      
      * small changes to markdown
      
      * Training and testing have the same integer encoding
      
      * Added debugger tool
      
      * added loss visualization
      
      * aded 1hot encoder and separated dataloader
      
      Added 1-hot encoder with scikit learn.
      Seperated the dataloader into a python file.
      
      * changes to get 99.998% accuracy
      
      * changed loss plot
      
      * accuracy at 70% after 50 epochs
      
      However, loss is not ok
      
      * got 75% accuracy
      
      * see loss
      
      * added scheduled statistics
      
      * added iterator over all possible parameters
      
      * updates on automation
      
      debugging model error
      
      * Delete cybersecurity-checkpoint.ipynb
      
      * Delete cybersecurity_2-checkpoint.ipynb
      
      * Delete exemplofixe-checkpoint.ipynb
      
      * Delete UNSW_NB15_testing-set.csv
      
      * Delete UNSW_NB15_train.csv
      
      * Delete UNSW_NB15_training-set.csv
      
      * Delete UNSW_NB15_val.csv
      
      * general cleanup
      
      * general cleanup
      
      * updates with 75.7238% accuracy
      
      * added quantization of the dataset
      
      * debugging the quantization of the dataset
      
      * added plots for the debugging
      
      * debugging the quantization. Show the differences
      
      * update debugging
      
      * updates on debugging
      
      * updates on debugging quantization
      
      * updates on debug, uint32 df added
      
      * updates on debugging
      
      * added 2 pictures for the debugging
      
      * Added quantization of the dataset
      
      * aded results for training the model with the quantized dataset
      
      * added quantization of the dataset
      
      * added new notebook with model definition with brevitas
      
      * cleaning up documents
      
      * modified the model definition
      
      * Changed the loss function
      
      * Added debug with pdb
      
      * Successfully created neural network with Brevitas
      
      * Correctly quantize the dataset
      
      * Added export of onnx model
      
      * Added FINN validation of the Brevitas model
      
      * improved dataloader
      
      * general cleanup
      
      * General Cleanup
      
      * General Cleanup
      
      * Completed verifying the FINN model against Brevitas
      
      * Added new layer to MLP - Debugging
      
      * verified that the MLP model with new layer (QuantIdentity) outputs the same in Brevitas and in FINN for all 82332 test inputs
      
      * verified that the MLP model with new layer (QuantIdentity) outputs the same in Brevitas and in FINN for all 82332 test inputs
      
      * verified that model with new layer (QuantIdentity) outputs the same in Brevitas and in FINN for all 82332 inputs
      
      * verified that model with new layer and input shifted to accept {-1,1}, outputs the same in Brevitas (input is in {-1,+1}) and in FINN (input is in {-1,+1})  for the 82332 inputs
      
      * General cleanup and added text
      
      * General cleanup: improved text
      
      * General cleanup: fixed text typos
      
      * General cleanup: Added text
      
      * Delete cybersecurity.ipynb
      
      * Delete dataloader.py
      
      * Rename cybersecurity_Brevitas_1bit.ipynb to 1-cybersecurity-Brevitas-1bit.ipynb
      
      * Rename cybersecurity_Brevitas_Verification.ipynb to 2-cybersecurity-finn-verification.ipynb
      
      * Added the last notebook
      
      * Added last notebook describing the finn build
      
      * Added changed parameters to see differences
      
      * Added changed parameters and added text
      
      * Fixed typo
      
      * [Notebooks] reorganize into folders, add README for cybsec
      
      * [Notebook] add license header and refs to cybsec dataset quantizer
      
      * [Notebooks] rename cybsec notebook files
      
      * [Notebook] first pass thru cybsec part 1
      
      * [Notebook] refactor more of cybsec part 1
      
      * [Notebook] add option to use pretrained weights
      
      * fixed outline and typo
      
      * [Notebook] update cybsec notebook #2 and gitignore
      
      * [Notebook] start refactoring cybsec part 3
      
      * [ConvertToHLS] allow out_scale=2 for bipolar MT
      
      * [Build] add alternative set of steps for estimation only
      
      * [Transform] attempt to handle padding for IODMAs
      
      * [Transform] explicitly ignore IODMA nodes for InsertDWC
      
      * [Notebook] full pass over cybsec notebook 3
      
      * [Util] move vivado utils into finn-base
      
      * fixed outline
      
      * [HLSCustomOp] better err msg on ipgen failure
      
      Co-authored-by: default avatarAlina Vasilciuc <alinav@xlnx.xilinx.com>
      Co-authored-by: default avatarYaman Umuroglu <yamanu@xilinx.com>
      
      * [Notebook] add README, remove mobilenet notebook
      
      * [Docs] round of updates
      
      * [Docs] make stack image local
      
      * [Docs] apidocs updates
      
      * [Docs] update README for v0.5b
      
      * [Release] merge dev into master for v0.5b
      
      * [Docs] bring back missing img
      
      * [Docs] bring back missing images
      
      * Switch hlslib comparison functions (#263)
      
      * [Test] add lfc to end2end tests
      
      * [Deps] update hlslib to get comp:: fxns
      
      * [HLS] use comp:: comparators instead of std::
      
      * [VVAU] hlslib now uses inner prod dim instead of K
      
      * [Thres] manually workaround vivado_hls bug for T[0][0]=0
      
      * [Infra] add .vscode to .gitignore
      
      * [Build] separate HLS codegen and ipgen steps (#265)
      
      * [Docs] first version of developer docs
      
      * [Notebook] fix broken resource paths
      
      * Fix Im2Col attributes for newer finn-base (#276)
      
      * [Deps] update finn-base
      
      * [Refactor] fix im2col props for updated finn-base
      
      * [Docs ] Add FAQ page to the Documentation (#273)
      
      * [Docs] Add FAQ page into the Docs
      
      * [Docs] some minor text format changes.
      
      * [Docs] updates to FAQ
      
      Co-authored-by: default avatarYaman Umuroglu <yaman.umuroglu@xilinx.com>
      
      * [Notebook] Added more descriptive text into the notebook
      
      * Fix ZCU102 support in Vivado shell project (#280)
      
      * [ConvertToHLS] fix conversion for bipolar outputs
      
      * [Notebook] updates to custom op notebook
      
      Co-authored-by: default avatarYaman Umuroglu <yamanu@xilinx.com>
      Co-authored-by: default avatarTobi-Alonso <tobi.alonso@gmail.com>
      Co-authored-by: default avataralinavalinav <60705229+alinavalinav@users.noreply.github.com>
      Co-authored-by: default avatarAlina Vasilciuc <alinav@xlnx.xilinx.com>
      Co-authored-by: default avatarYaman Umuroglu <yaman.umuroglu@xilinx.com>
      Co-authored-by: default avatarFelix Jentzsch <45395194+fpjentzsch@users.noreply.github.com>
      
      Co-authored-by: default avatarjalezeta <51440887+jalezeta@users.noreply.github.com>
      Co-authored-by: default avatarTobi-Alonso <tobi.alonso@gmail.com>
      Co-authored-by: default avataralinavalinav <60705229+alinavalinav@users.noreply.github.com>
      Co-authored-by: default avatarAlina Vasilciuc <alinav@xlnx.xilinx.com>
      Co-authored-by: default avatarFelix Jentzsch <45395194+fpjentzsch@users.noreply.github.com>
      a65e08b0
  2. Feb 12, 2021
  3. Feb 11, 2021
  4. Feb 07, 2021
  5. Feb 06, 2021
  6. Feb 01, 2021
  7. Jan 26, 2021
  8. Jan 21, 2021
  9. Jan 20, 2021
  10. Jan 17, 2021
    • Yaman Umuroglu's avatar
      Switch hlslib comparison functions (#263) · 8497814b
      Yaman Umuroglu authored
      * [Test] add lfc to end2end tests
      
      * [Deps] update hlslib to get comp:: fxns
      
      * [HLS] use comp:: comparators instead of std::
      
      * [VVAU] hlslib now uses inner prod dim instead of K
      
      * [Thres] manually workaround vivado_hls bug for T[0][0]=0
      8497814b
  11. Jan 15, 2021
  12. Dec 17, 2020
    • Yaman Umuroglu's avatar
      [Docs] bring back missing images · af783db8
      Yaman Umuroglu authored
      af783db8
    • Yaman Umuroglu's avatar
      [Docs] bring back missing img · 61e80f2d
      Yaman Umuroglu authored
      61e80f2d
    • Yaman Umuroglu's avatar
      4fee6ffd
    • Yaman Umuroglu's avatar
      [Docs] update README for v0.5b · e6236e38
      Yaman Umuroglu authored
      e6236e38
    • Yaman Umuroglu's avatar
      [Docs] apidocs updates · b7da30f7
      Yaman Umuroglu authored
      b7da30f7
    • Yaman Umuroglu's avatar
      [Docs] make stack image local · 5224f12a
      Yaman Umuroglu authored
      5224f12a
    • Yaman Umuroglu's avatar
      [Docs] round of updates · fafde712
      Yaman Umuroglu authored
      fafde712
    • Yaman Umuroglu's avatar
      be5fd122
    • alinavalinav's avatar
      Feature/cybersecurity notebook (#259) · 004475a4
      alinavalinav authored
      
      * Created cybersecurity notebook and downloaded data with wget
      
      * Reorganized the cybersecurity notebook
      
      * Read the entire dataset as a pytorch tensor and trained a simple MLP on the UNSW_NB15 dataset
      
      * small changes to markdown
      
      * Training and testing have the same integer encoding
      
      * Added debugger tool
      
      * added loss visualization
      
      * aded 1hot encoder and separated dataloader
      
      Added 1-hot encoder with scikit learn.
      Seperated the dataloader into a python file.
      
      * changes to get 99.998% accuracy
      
      * changed loss plot
      
      * accuracy at 70% after 50 epochs
      
      However, loss is not ok
      
      * got 75% accuracy
      
      * see loss
      
      * added scheduled statistics
      
      * added iterator over all possible parameters
      
      * updates on automation
      
      debugging model error
      
      * Delete cybersecurity-checkpoint.ipynb
      
      * Delete cybersecurity_2-checkpoint.ipynb
      
      * Delete exemplofixe-checkpoint.ipynb
      
      * Delete UNSW_NB15_testing-set.csv
      
      * Delete UNSW_NB15_train.csv
      
      * Delete UNSW_NB15_training-set.csv
      
      * Delete UNSW_NB15_val.csv
      
      * general cleanup
      
      * general cleanup
      
      * updates with 75.7238% accuracy
      
      * added quantization of the dataset
      
      * debugging the quantization of the dataset
      
      * added plots for the debugging
      
      * debugging the quantization. Show the differences
      
      * update debugging
      
      * updates on debugging
      
      * updates on debugging quantization
      
      * updates on debug, uint32 df added
      
      * updates on debugging
      
      * added 2 pictures for the debugging
      
      * Added quantization of the dataset
      
      * aded results for training the model with the quantized dataset
      
      * added quantization of the dataset
      
      * added new notebook with model definition with brevitas
      
      * cleaning up documents
      
      * modified the model definition
      
      * Changed the loss function
      
      * Added debug with pdb
      
      * Successfully created neural network with Brevitas
      
      * Correctly quantize the dataset
      
      * Added export of onnx model
      
      * Added FINN validation of the Brevitas model
      
      * improved dataloader
      
      * general cleanup
      
      * General Cleanup
      
      * General Cleanup
      
      * Completed verifying the FINN model against Brevitas
      
      * Added new layer to MLP - Debugging
      
      * verified that the MLP model with new layer (QuantIdentity) outputs the same in Brevitas and in FINN for all 82332 test inputs
      
      * verified that the MLP model with new layer (QuantIdentity) outputs the same in Brevitas and in FINN for all 82332 test inputs
      
      * verified that model with new layer (QuantIdentity) outputs the same in Brevitas and in FINN for all 82332 inputs
      
      * verified that model with new layer and input shifted to accept {-1,1}, outputs the same in Brevitas (input is in {-1,+1}) and in FINN (input is in {-1,+1})  for the 82332 inputs
      
      * General cleanup and added text
      
      * General cleanup: improved text
      
      * General cleanup: fixed text typos
      
      * General cleanup: Added text
      
      * Delete cybersecurity.ipynb
      
      * Delete dataloader.py
      
      * Rename cybersecurity_Brevitas_1bit.ipynb to 1-cybersecurity-Brevitas-1bit.ipynb
      
      * Rename cybersecurity_Brevitas_Verification.ipynb to 2-cybersecurity-finn-verification.ipynb
      
      * Added the last notebook
      
      * Added last notebook describing the finn build
      
      * Added changed parameters to see differences
      
      * Added changed parameters and added text
      
      * Fixed typo
      
      * [Notebooks] reorganize into folders, add README for cybsec
      
      * [Notebook] add license header and refs to cybsec dataset quantizer
      
      * [Notebooks] rename cybsec notebook files
      
      * [Notebook] first pass thru cybsec part 1
      
      * [Notebook] refactor more of cybsec part 1
      
      * [Notebook] add option to use pretrained weights
      
      * fixed outline and typo
      
      * [Notebook] update cybsec notebook #2 and gitignore
      
      * [Notebook] start refactoring cybsec part 3
      
      * [ConvertToHLS] allow out_scale=2 for bipolar MT
      
      * [Build] add alternative set of steps for estimation only
      
      * [Transform] attempt to handle padding for IODMAs
      
      * [Transform] explicitly ignore IODMA nodes for InsertDWC
      
      * [Notebook] full pass over cybsec notebook 3
      
      * [Util] move vivado utils into finn-base
      
      * fixed outline
      
      * [HLSCustomOp] better err msg on ipgen failure
      
      Co-authored-by: default avatarAlina Vasilciuc <alinav@xlnx.xilinx.com>
      Co-authored-by: default avatarYaman Umuroglu <yamanu@xilinx.com>
      004475a4
  13. Dec 16, 2020
  14. Dec 14, 2020
  15. Dec 13, 2020
    • Yaman Umuroglu's avatar
      0fdc690b
    • Yaman Umuroglu's avatar
      [Driver] handle case with no rt weights · 72bd1487
      Yaman Umuroglu authored
      72bd1487
    • Yaman Umuroglu's avatar
      Driver data packing + improvements (#261) · e202bca2
      Yaman Umuroglu authored
      * [Driver] add driver_base.py as own template file + comments
      
      * [Driver] also move validation to won template + use in transform
      
      * [Driver] more comments
      
      * [Driver] suggested updates from PYNQ team + async mode exec_on_buffers
      
      * [Driver] allow smaller batchsize in execute_on_buffers
      
      * [Driver] optimize buffer alloc a bit
      
      * [Driver] wait condition fix
      
      * [Deps] update finn-base
      
      * [Deps] update finn-base
      
      * [Driver] enable fast_mode, expose more benchmarks
      
      * [Deps] update finn-base
      e202bca2
    • Yaman Umuroglu's avatar
      Build step: measure rtlsim performance (#262) · 72b11ca6
      Yaman Umuroglu authored
      * [Build] introduce step_measure_rtlsim_performance
      
      * [Docs] document the rtlsim performance step
      
      * [Docs] add comments on CPU/RAM/storage recommandations
      
      * [Build, Test] enable rtlsim perf as part of build test too
      
      * [Build] print where intermediate outputs are generated
      
      * [Docs] remove ghpages content, add note
      
      * [Docker] use -c continue for build_custom mode
      
      * [Docs] minor fixes
      72b11ca6
  16. Dec 09, 2020
  17. Dec 08, 2020
    • Yaman Umuroglu's avatar
    • Yaman Umuroglu's avatar
    • Yaman Umuroglu's avatar
    • Yaman Umuroglu's avatar
      [Build] add verification to build steps · 4d496031
      Yaman Umuroglu authored
      4d496031
    • Yaman Umuroglu's avatar
    • Yaman Umuroglu's avatar
      f7bc42b1
    • Yaman Umuroglu's avatar
      Support runtime weights & thresholds in generated driver (#256) · 3cfa1896
      Yaman Umuroglu authored
      * [Build] add a deployment_package step
      
      * [Build] typo fix in build examples
      
      * [Build] fix deployment_package step
      
      * [Analysis] ensure python integers in fpgadataflow analysis passes
      
      * [Build] report generation and other minor improvements
      
      * [Docs] update build_dataflow docs
      
      * [Build] latency est. fix
      
      * [Build] check if fold config is None
      
      * [Build] add ooc synthesis step
      
      * [Deps] update finn-base
      
      * [Util] out_of_context_synth: remove remote, use launch_process_helper
      
      * [Build] include all outputs in examples configs
      
      * [Docs] update build flow docs
      
      * [Deps] update finn-base
      
      * [Util] bugfix in launch_process_helper call
      
      * [Docker] use interactive mode for builds
      
      * [Build] enable pdb debugging for builds
      
      * [Refactor] move build functions to own submodule
      
      * [Test] build_dataflow: fix expected files
      
      * [Build] report estimated resource total
      
      * [Infra] remove old eggs
      
      * [HLSCustomOp] introduce get_op_counts
      
      only implemented for MVAU and VVAU for now
      
      * [HLSCustomOp] extend get_op_counts to include params too
      
      * [Analysis] introduce op_and_param_counts pass
      
      * [Build] generate op/param counts as part of estimates + add doc
      
      * [HLSCustomOp] assert if ap_int_max_w is too large
      
      * [StreamingFC] fix ap_int_max_w calculation
      
      * [Build] minor fix in step_generate_estimate_reports
      
      * [StreamingFC] enable decoupled URAM weights
      
      * [StreamingFC export 0-valued .dat for decoupled uram
      
      * [Zynq] bugfix: AXI MM and lite IF counts were switched around
      
      * [Zynq] support wiring up multiple AXI lites in shell
      
      * [Deps] update finn-base
      
      * [HLSCustomOp] introduce uram_efficiency_estimation
      
      * [StreamingFC] implement uram eff est
      
      * [FIFO] fix ip packaging problems
      
      * [Thres] better integer check for thresholds
      
      * [HLSCustomOp] rework infer_node_datatype to be more flexible
      
      allow re-setting of inputDataType if it changed during datatype
      inference
      
      * [Thres] bugfix in integer thres check
      
      * [Thres] bugfix in integer thres check
      
      * [Docker] relax instance name, only fwd ports in notebook mode
      
      * [Driver] generate runtime weight files for appropriate layers
      
      * [Driver] draft a first version of load_runtime_weights
      
      * [Driver] fixes&enhancements to load_runtime_weights
      
      * [Driver] typo fix in split
      
      * [Test] use runtime weights for tfc end2end
      
      * [Build] bugfix in ooc step
      
      * [Driver] also handle runtime-writable thresholds
      
      * [Thresholding] implement get_op_and_param_counts
      
      * [Test] use tfc-w1a1 as standalone thresholds end2end testcase
      
      * [Build] add option for standalone thresholds
      
      * [Driver] update comments
      
      * [Driver] overhaul driver, split up template
      
      * [Test] fix test_res_estimate expectation
      
      * [Driver] fix varname in template
      3cfa1896
  18. Dec 03, 2020
    • Yaman Umuroglu's avatar
      Dataflow build additions (#253) · 884cb146
      Yaman Umuroglu authored
      * [Build] add a deployment_package step
      
      * [Build] typo fix in build examples
      
      * [Build] fix deployment_package step
      
      * [Analysis] ensure python integers in fpgadataflow analysis passes
      
      * [Build] report generation and other minor improvements
      
      * [Docs] update build_dataflow docs
      
      * [Build] latency est. fix
      
      * [Build] check if fold config is None
      
      * [Build] add ooc synthesis step
      
      * [Deps] update finn-base
      
      * [Util] out_of_context_synth: remove remote, use launch_process_helper
      
      * [Build] include all outputs in examples configs
      
      * [Docs] update build flow docs
      
      * [Deps] update finn-base
      
      * [Util] bugfix in launch_process_helper call
      
      * [Docker] use interactive mode for builds
      
      * [Build] enable pdb debugging for builds
      
      * [Refactor] move build functions to own submodule
      
      * [Test] build_dataflow: fix expected files
      
      * [Build] report estimated resource total
      
      * [Infra] remove old eggs
      
      * [HLSCustomOp] introduce get_op_counts
      
      only implemented for MVAU and VVAU for now
      
      * [HLSCustomOp] extend get_op_counts to include params too
      
      * [Analysis] introduce op_and_param_counts pass
      
      * [Build] generate op/param counts as part of estimates + add doc
      
      * [HLSCustomOp] assert if ap_int_max_w is too large
      
      * [StreamingFC] fix ap_int_max_w calculation
      
      * [Build] minor fix in step_generate_estimate_reports
      884cb146
    • Tobi-Alonso's avatar
      Set vivado DWC input width explicitly as by default a block will have a 1 byte... · b9300a8d
      Tobi-Alonso authored
      Set vivado DWC input width explicitly as by default a block will have a 1 byte input which probably will cause a bottleneck (#254)
      
      b9300a8d
  19. Dec 01, 2020
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