======================================================================== loading model ======================================================================== Loading weights: 0%| | 0/1013 [00:00 2048 ratio 19.71x (linear ~8x, launch-bound ~1x, quadratic ~64x) 16384 -> 8192 ratio 3.03x (linear ~2x, quadratic ~4x) ======================================================================== B. PADDING PENALTY (same real tokens, with vs without pad) ======================================================================== 2 x 16,384 no padding 35.244 s kept=26048 peak= 76.6 GiB 2 x 16,384 50% pad on row 1 38.567 s kept=19640 peak= 77.8 GiB ======================================================================== C. ISOLATED CE WALL CLOCK ======================================================================== 2 x 16,384 (CE timed) 35.329 s kept=26210 peak= 76.6 GiB CE=374 ms (1.1%) 2 x 4,096 (CE timed) 4.387 s kept=6512 peak= 55.3 GiB CE=93 ms (2.1%) ======================================================================== D. KERNEL TABLE - one fwd+bwd at 2 x 16,384 ======================================================================== USDT:2026-08-24 22:03:51 574811:574811 SyncActivityProfilerHandler.cpp:52] profiler_start USDT:2026-08-24 22:04:27 574811:574811 SyncActivityProfilerHandler.cpp:59] profiler_stop ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ aten::_efficient_attention_backward 0.00% 573.671us 0.00% 1.681ms 56.028us 16.145s 45.71% 16.156s 538.546ms 30 fmha_cutlassB_bf16_aligned_128x64_k65536_sm80(PyTorc... 0.00% 0.000us 0.00% 0.000us 0.000us 16.145s 45.71% 16.145s 538.152ms 30 aten::_efficient_attention_forward 0.00% 795.660us 0.01% 1.933ms 32.218us 6.691s 18.94% 6.691s 111.519ms 60 fmha_cutlassF_bf16_aligned_32x128_gmem_sm80(PyTorchM... 0.00% 0.000us 0.00% 0.000us 0.000us 6.691s 18.94% 6.691s 111.519ms 60 aten::mm 0.51% 180.757ms 0.77% 270.268ms 10.614us 3.745s 10.60% 3.745s 147.063us 25463 aten::mul 0.13% 45.428ms 0.18% 64.624ms 12.129us 2.721s 7.70% 2.721s 510.606us 5328 aten::copy_ 0.06% 19.823ms 92.46% 32.574s 6.100ms 1.977s 5.60% 1.977s 370.189us 5340 void cutlass::Kernel2(... 0.00% 0.000us 0.00% 0.000us 0.000us 351.768ms 1.00% 351.768ms 1.933ms 182 Memcpy DtoD (Device -> Device) 0.00% 0.000us 0.00% 0.000us 0.000us 341.588ms 0.97% 341.588ms 634.922us 538 aten::pow 0.06% 21.418ms 0.11% 37.019ms 18.659us 332.072ms 0.94% 493.271ms 248.624us 1984 void at::native::vectorized_elementwise_kernel<4, at... 0.00% 0.000us 0.00% 0.000us 0.000us 330.315ms 0.94% 330.315ms 499.720us 661 void at::native::vectorized_elementwise_kernel<4, at... 0.00% 0.000us 0.00% 0.000us 0.000us 316.108ms 0.89% 316.108ms 383.161us 825 aten::sum 0.01% 5.258ms 0.02% 7.700ms 13.461us 286.461ms 0.81% 286.464ms 500.811us 572 aten::native_dropout 0.02% 6.453ms 0.03% 11.139ms 27.168us 258.244ms 0.73% 258.244ms 629.865us 410 void at::native::(anonymous namespace)::fused_dropou... 0.00% 0.000us 0.00% 0.000us 0.000us 258.244ms 0.73% 258.244ms 629.865us 410 void at::native::unrolled_elementwise_kernel(char*, 182 351.8 Memcpy DtoD (Device -> Device) 538 341.6 aten::pow 1984 332.1 void at::native::vectorized_elementwise_kernel<4, at::nati 661 330.3 void at::native::vectorized_elementwise_kernel<4, at::nati 825 316.1 aten::sum 572 286.5 aten::native_dropout 410 258.2 void at::native::(anonymous namespace)::fused_dropout_kern 410 258.2 void at::native::unrolled_elementwise_kernel