zxybazh commented on PR #12648: URL: https://github.com/apache/tvm/pull/12648#issuecomment-1231920134
Follow up with CUDA benchmarking results on Geforce RTX 3070, all data layouts are `NCHW`, padding `(1, 1)`, kernel size `(3, 3)`. Workload is a single conv2d function, dispatched to `nn.contrib_conv2d_winograd_without_weight_transform` for both AutoTVM and MetaSchedule. <table class="table table-bordered table-hover table-condensed"> <thead><tr><th title="Field #1">Data Shape</th> <th title="Field #2">Kernel Layout</th> <th title="Field #3">Kernel Shape</th> <th title="Field #4">Winograd</th> <th title="Field #5">MS trials</th> <th title="Field #6">AutoTVM trials</th> <th title="Field #7">MS Perf(ms)</th> <th title="Field #8">AutoTVM Perf(ms)</th> <th title="Field #9">Perf Compare</th> </tr></thead> <tbody><tr> <td>(1, 512, 7, 7)</td> <td>OIHW</td> <td>(512, 512, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.05053524796891558</td> <td>0.05030714765801846</td> <td align="right">-0.4513687378%</td> </tr> <tr> <td>(2, 64, 56, 56)</td> <td>OIHW</td> <td>(64, 64, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.040951505223880594</td> <td>0.04111647433704021</td> <td align="right">0.4028401698%</td> </tr> <tr> <td>(2, 48, 56, 56)</td> <td>OIHW</td> <td>(48, 48, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.029897891745708238</td> <td>0.030240458663465385</td> <td align="right">1.1457895449%</td> </tr> <tr> <td>(1, 64, 28, 28)</td> <td>OIHW</td> <td>(64, 64, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.010250015296394941</td> <td>0.010370220173567484</td> <td align="right">1.1727287589%</td> </tr> <tr> <td>(1, 128, 28, 28)</td> <td>OIHW</td> <td>(128, 128, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.026061056047912482</td> <td>0.02657971123398702</td> <td align="right">1.9901541408%</td> </tr> <tr> <td>(1, 64, 56, 56)</td> <td>OIHW</td> <td>(64, 64, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.022871235249414843</td> <td>0.023843754776970795</td> <td align="right">4.2521513025%</td> </tr> <tr> <td>(1, 128, 14, 14)</td> <td>OIHW</td> <td>(128, 128, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.011837556120361336</td> <td>0.012637039015519788</td> <td align="right">6.7537833572%</td> </tr> <tr> <td>(1, 256, 14, 14)</td> <td>OIHW</td> <td>(256, 256, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.028101132421289355</td> <td>0.03071125413188647</td> <td align="right">9.2883150453%</td> </tr> <tr> <td>(1, 80, 73, 73)</td> <td>OIHW</td> <td>(192, 80, 3, 3)</td> <td>Yes</td> <td align="right">2048</td> <td align="right">1024</td> <td>0.2016123825065274</td> <td>0.22382275871015564</td> <td align="right">11.0163750497%</td> </tr> </tbody></table> -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
