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jmduarte avatar jmduarte commented on May 13, 2024

Somehow the issue comes from re-writing the mult array as a 1D array instead of a 2D array:

d90e74a#diff-b37c065f136460b015788b96b5c25102L96

Conversely if I comment out the mult array partitioning (much like the weight array is not partitioned), it also works again (although I see some other warnings)
https://github.com/hls-fpga-machine-learning/hls4ml/blob/d90e74a7c92eb63e675e27396177cb05b9286f00/nnet_utils/nnet_layer.h#L70

Maybe it would help if I knew why the weight array partitioning was commented out. It looks like @benjaminkreis did it?

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benjaminkreis avatar benjaminkreis commented on May 13, 2024

Re weight array partition:
#17 (comment)

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nhanvtran avatar nhanvtran commented on May 13, 2024

just to record this for everyone...

So this error actually looks like a difference in Vivado version. This does not occur with 2017.2. It looks like Xilinx added an array size limit for fully partitioning in 2018.2 -- probably because of our complaints about RAM limits in the compiler 😱

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SteCla0 avatar SteCla0 commented on May 13, 2024

Error still exists with 16x100x100x100x100x5 example in hls4ml v0.6.0 and vivado 2020.1

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jmduarte avatar jmduarte commented on May 13, 2024

Hi @SteCla0, if you want to discuss, can you use the Discussions?

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