FrozenGene commented on pull request #5485: URL: https://github.com/apache/incubator-tvm/pull/5485#issuecomment-625176840
> @FrozenGene > We made the following tests to go through all the layouts, > > Layout_1(the same in this PR) > input_tile = (P, CI, alpha, alpha) > data_pack = (alpha, alpha, P, CI) > bgemm = (alpha, alpha, P, CO) > inverse = (P, CO, m, m) > output = (N, H, W, CO) > kernel = (alpha, alpha, CI, CO) > > Layout_2 > input_tile = (P, CI, alpha, alpha) > data_pack = (alpha, alpha, P, CI) > bgemm = (alpha, alpha, P, CO) > inverse = (P, CO, m, m) > output = (N, H, W, CO) > kernel = (alpha, alpha, CO, CI) > > Layout_3 > input_tile = (alpha, alpha, P, CI) > data_pack = (alpha, alpha, P, CI) > bgemm = (alpha, alpha, P, CO) > inverse = (P, CO, m, m) > output = (N, H, W, CO) > kernel = (alpha, alpha, CI, CO) > > Layout_4 > input_tile = (alpha, alpha, P, CI) > data_pack = (alpha, alpha, P, CI) > bgemm = (alpha, alpha, P, CO) > inverse = (m, m, P, CO) > output = (N, H, W, CO) > kernel = (alpha, alpha, CO, CI) > > The results are listed below. > > kernel:3x3x64x64 feature maps:56x56x64: > > batch layout_1 layout_2 layout_3 layout_4 > 1 0.0762 0.0766 0.0758 0.0907 > 2 0.0911 0.0931 0.0957 0.0939 > 4 0.1197 0.124 0.1188 0.1257 > 8 0.1979 0.1942 0.2026 0.2208 > 16 0.3453 0.3577 0.3427 0.3833 > 32 0.6613 0.7161 0.6615 0.7574 > 256 5.5837 5.3269 5.772 5.7058 > kernel:3x3x256x256 feature maps:14x14x256: > > batch layout_1 layout_2 layout_3 layout_4 > 1 0.0633 0.0694 0.0703 0.656 > 2 0.0825 0.0835 0.0822 0.851 > 4 0.1417 0.1562 0.1382 0.1502 > 8 0.1829 0.1853 0.1833 0.182 > 16 0.264 0.277 0.2832 0.2621 > 32 0.4506 0.4799 0.4507 0.4773 > 256 3.9432 4.0867 3.5088 4.5032 > Note: weight transform was pre-computed. The benchmarks were running on T4 GPU (16GB, 70W). Latency is reported with unit of ms. > > We can see that the performance of all layouts are in the same level. Make sense to me. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
