liangfu edited a comment on issue #4392: [VTA] Enable streamlined GEMM execution URL: https://github.com/apache/incubator-tvm/pull/4392#issuecomment-557371295 This PR doesn't intend to reduce cycle count, or any performance improvement. My major intention is to bring successful evaluation of `matrix_multiply_opt.py` and `convolution_opt.py` scripts, so that we can get closer to bring end-to-end support in evaluating resnet18. The reason the evaluation of these scripts failed previously is that > This PR fixed an issue in the streamlined GEMM execution by disabling pipelined adder, which consumes 4 cycles (in case of LOG_BLOCK=4) in addition to the single-cycle fused multiplier-adder. This is much longer than the 4-stage streamline design in the TensorGemm module. Here are the benchmarks from Intel's Timing Analyzer (, with **cycle count** and **result** entry performed with `matrix_multiply_opt.py` script). | design | area (in ALMs) | fmax (slow 100C) | fmax (slow -40C) | fmax (fast 100C) | fmax (fast -40C) | cycle count | result | | -- | -- | -- | -- | -- | -- | -- | -- | | PipeAdderX4 | 20,419/41,910 (49%) | **71.74 MHz** | 73.52 MHz | 109.12 MHz | 135.46 MHz | 183,038 | fail | | PipeAdderX1 AdderX3 | 19,811/41,910 (47%) | **65.71 MHz** | 68.54 MHz | 106.3 MHz | 130.82 MHz | 182,990 | pass | | AdderX4 | 18,186/41,910 (43%) | 60.72 MHz | **58.82 MHz** | 92.43 MHz | 114.97 MHz | 182,990 | pass |
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