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Analytical FIFO sizing #1185

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FIFO sizing is an extremely time-consuming process in terms of CPU cycles due to currently requiring RTL simulation of a model to determine the FIFO depths by tracking the behavior of the model.

Currently, FINN uses two main approaches for FIFO sizing:

The global sizing algorithm which incrementally tightens FIFO sizes while rerunning RTLSIM until a steady-state is reached of the entire model. (AutoFIFOSizingMethod.LARGEFIFO_RTLSIM)
The characteristic-function based approach which RTL simulates individual nodes and constructs characteristic functions for each one and then uses phase-shifting to determine an optimal FIFO size by finding how many cycles the input characteristic function must be shifted forward before it reaches a steady state with the output stream. (AutoFIFOSizingMethod.CHARACTERIZE)
Between these two options, the later - characteristic sizing can be dramatically sped up by computing the characteristic functions of individual nodes analytically, rather than by using RTLSIM.

This can be accomplished by manually reviewing the RTL (or HLS) code of each node and constructing a model python function which reproduces the loop behavior of only the AXI stream reads and writes, filling up the characteristic function array.

The PR includes these python-based model functions as part of the custom_ops classes of the following nodes:

  • channelwise_op
  • convolutioninputgenerator
  • fmpadding
  • labelselect
  • matrixvectoractivation
  • pool
  • streamingdatawidthconverter (generalized variant, very conservative estimate)
  • streamingmaxpool
  • thresholding
  • vectorvectoractivation

Additionally, it includes modifications to /builder/build_dataflow_config.py and builder/build_dataflow_steps.py so that vivado is not called in the FIFO sizing step unless there is no characteristic function for an a node (and in that case it called to only characterize that respective node). This is achieved by introducing a new 'ipgen_ignore' node argument, which is set to true for all analytically characterized nodes once FIFO sizing is started and will force the FINN compiler to skip calling Vivado. This argument set back to false, allowing to call Vivado once the analytic FIFO sizing is finished.

Improvements to be made:

The remaining nodes in FINN should be characterized as necessary
There might exist parameter configurations for the convolutioninputgenerator and streamingmaxpool nodes where the characteristic function is inaccurate since an exhaustive search is complicated to do automatically.
Currently, the test for fifo sizing tests for exact correctness of the analytical function relative to the RTLSIM output. However, small latencies introduced at the start or end of the characteristic function by HLS do not lead to a change in final FIFO sizes. The test should be changed to compare the characteristic functions in a more relaxed manner. This would then allow to also perform an exhaustive test of all possible configurations for the nodes.
The characteristic FIFO sizing algorithm lacks support for branching networks. This is irrespective of the individual characteristic functions and should be improved in the main FIFO sizing function (transformation/derive_characteristic.py)

lstasytis and others added 6 commits September 16, 2024 14:22
…tgenerator, fmpadding, labelselect, matrixvectoractivation, pool, streamingdatawidthconverter (generalized variant, very conservative estimate), streamingmaxpool, thresholding, vectorvectoractivation
Signed-off-by: lstasytis <[email protected]>
@lstasytis lstasytis marked this pull request as ready for review October 15, 2024 16:11
@auphelia auphelia self-requested a review October 24, 2024 08:37
…ing and specific cases of streamingmaxpool and slidingwindow
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2 participants