source_file stringclasses 73
values | source_kind stringclasses 2
values | gpu_name stringclasses 10
values | gpu_uuid stringclasses 11
values | seed int64 11 22 | model_key stringclasses 9
values | model_label stringclasses 9
values | actual_unique_parameters float64 150M 7.98B ⌀ | sequence_length int64 512 32.8k | batch_size float64 1 512 ⌀ | tokens_per_step float64 1.02k 131k ⌀ | status stringclasses 3
values | stable bool 1
class | warmup_steps_executed float64 11 45 ⌀ | measured_steps float64 20 20 ⌀ | median_step_time_ms float64 42.4 3.59k ⌀ | mean_based_tokens_per_second float64 3.64k 244k ⌀ | measured_robust_relative_jitter float64 0 0.06 ⌀ | tokens_per_second float64 3.64k 244k ⌀ | achieved_tflops float64 19.8 668 ⌀ | dense_bf16_peak_tflops float64 155 2.25k | model_flops_utilization_pct float64 0.88 100 ⌀ | configured_clock_dense_bf16_peak_tflops float64 181 2.25k | configured_clock_model_flops_utilization_pct float64 0.88 78 ⌀ | peak_allocated_gb float64 4.62 286 ⌀ | peak_allocated_vram_pct float64 1.61 99.6 ⌀ | peak_reserved_gb float64 4.66 287 ⌀ | peak_reserved_vram_pct float64 1.62 99.7 ⌀ | selected_sdpa_backend stringclasses 1
value | error stringclasses 553
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b300_training_seed22_v2.json | baseline_reused | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 82.572639 | 49,591.198865 | 0.003932 | 49,604.808887 | 138.661787 | 2,250 | 6.162746 | 2,250 | 6.162746 | 12.896346 | 4.486799 | 13.230932 | 4.603206 | FLASH_ATTENTION | null |
b300_training_seed22_v2.json | baseline_reused | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 106.829952 | 76,622.005313 | 0.001236 | 76,682.614082 | 214.353176 | 2,250 | 9.526808 | 2,250 | 9.526808 | 20.89 | 7.267891 | 21.495808 | 7.478659 | FLASH_ATTENTION | null |
b300_training_seed22_v2.json | baseline_reused | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 173.268196 | 94,552.437834 | 0.00032 | 94,558.611264 | 264.322479 | 2,250 | 11.747666 | 2,250 | 11.747666 | 36.877308 | 12.830074 | 38.052823 | 13.239051 | FLASH_ATTENTION | null |
b300_training_seed22_v2.json | baseline_reused | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 2,048 | 16 | 32,768 | complete | true | 11 | 20 | 306.25975 | 106,498.886159 | 0.000294 | 106,994.144548 | 299.083892 | 2,250 | 13.292617 | 2,250 | 13.292617 | 68.851926 | 23.954441 | 71.420609 | 24.848118 | FLASH_ATTENTION | null |
b300_training_seed22_v2.json | baseline_reused | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 2,048 | 32 | 65,536 | complete | true | 11 | 20 | 564.387238 | 116,048.611893 | 0.000447 | 116,118.855353 | 324.590466 | 2,250 | 14.426243 | 2,250 | 14.426243 | 132.80116 | 46.203176 | 137.66964 | 47.896981 | FLASH_ATTENTION | null |
b300_training_seed22_v2.json | baseline_reused | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 2,048 | 64 | 131,072 | complete | true | 11 | 20 | 1,079.055298 | 121,457.647201 | 0.00025 | 121,469.215026 | 339.546484 | 2,250 | 15.090955 | 2,250 | 15.090955 | 260.699628 | 90.700644 | 270.088012 | 93.966979 | FLASH_ATTENTION | null |
rtx4090_training_seed11_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 11 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 85.102882 | 24,060.27069 | 0.002245 | 24,064.989841 | 67.269577 | 165.2 | 40.720083 | 205.516667 | 32.731933 | 8.899502 | 35.230138 | 8.969519 | 35.507312 | FLASH_ATTENTION | null |
rtx4090_training_seed11_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 11 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 142.826637 | 28,675.65545 | 0.000588 | 28,678.123901 | 80.164807 | 165.2 | 48.525912 | 205.516667 | 39.006475 | 12.896346 | 51.052299 | 13.230932 | 52.376814 | FLASH_ATTENTION | null |
rtx4090_training_seed11_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 11 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 279.315704 | 29,249.568766 | 0.000692 | 29,328.819943 | 81.983717 | 165.2 | 49.626947 | 205.516667 | 39.891517 | 20.89 | 82.69649 | 21.495808 | 85.094681 | FLASH_ATTENTION | null |
rtx4090_training_seed11_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 11 | 350m | 350M | 348,447,744 | 2,048 | 8 | null | oom | null | null | null | null | null | null | null | null | 165.2 | null | 205.516667 | null | 24.628364 | 97.495419 | 24.698159 | 97.771713 | null | CUDA out of memory. Tried to allocate 88.00 MiB. GPU 0 has a total capacity of 23.53 GiB of which 57.69 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.94 GiB is allocated by PyTorch, and 66.56 MiB is reserved by PyTorch but unallocated. If reserved but un... |
rtx4090_training_seed22_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 22 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 85.002514 | 24,086.532449 | 0.001941 | 24,093.405082 | 67.349007 | 165.2 | 40.768164 | 205.516667 | 32.770582 | 8.899502 | 35.230138 | 8.969519 | 35.507312 | FLASH_ATTENTION | null |
rtx4090_training_seed22_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 142.746994 | 28,683.376844 | 0.001081 | 28,694.124371 | 80.209533 | 165.2 | 48.552986 | 205.516667 | 39.028238 | 12.896346 | 51.052299 | 13.230932 | 52.376814 | FLASH_ATTENTION | null |
rtx4090_training_seed22_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 279.307861 | 29,326.737379 | 0.000377 | 29,329.643502 | 81.986019 | 165.2 | 49.628341 | 205.516667 | 39.892637 | 20.89 | 82.69649 | 21.495808 | 85.094681 | FLASH_ATTENTION | null |
rtx4090_training_seed22_v2.json | baseline_reused | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | null | oom | null | null | null | null | null | null | null | null | 165.2 | null | 205.516667 | null | 24.628364 | 97.495419 | 24.698159 | 97.771713 | null | CUDA out of memory. Tried to allocate 88.00 MiB. GPU 0 has a total capacity of 23.53 GiB of which 57.69 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.94 GiB is allocated by PyTorch, and 66.56 MiB is reserved by PyTorch but unallocated. If reserved but un... |
rtx5090_training_seed11.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 11 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 68.99939 | 29,669.981632 | 0.000623 | 29,681.421972 | 82.969356 | 209.5 | 39.603511 | 268.946822 | 30.849725 | 8.899502 | 26.432444 | 8.969519 | 26.640402 | null | null |
rtx5090_training_seed11.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 11 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 109.099167 | 37,543.800846 | 0.000242 | 37,543.824738 | 104.947362 | 209.5 | 50.094206 | 268.946822 | 39.021603 | 12.896346 | 38.303484 | 13.230932 | 39.29724 | null | null |
rtx5090_training_seed11.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 11 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 198.135178 | 41,341.282907 | 0.000363 | 41,345.510165 | 115.574326 | 209.5 | 55.166743 | 268.946822 | 42.972929 | 20.89 | 62.045466 | 21.495808 | 63.844779 | null | null |
rtx5090_training_seed11.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 11 | 350m | 350M | 348,447,744 | 2,048 | 8 | null | oom | null | null | null | null | null | null | null | null | 209.5 | null | 268.946822 | null | 32.685051 | 97.077991 | 32.809943 | 97.448934 | null | CUDA out of memory. Tried to allocate 1000.00 MiB. GPU 0 has a total capacity of 31.36 GiB of which 247.88 MiB is free. Including non-PyTorch memory, this process has 31.11 GiB memory in use. Of the allocated memory 30.44 GiB is allocated by PyTorch, and 79.11 MiB is reserved by PyTorch but unallocated. If reserved but... |
rtx5090_training_seed22.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 22 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 69.01408 | 29,672.673609 | 0.000535 | 29,675.103958 | 82.951695 | 209.5 | 39.595081 | 268.946822 | 30.843159 | 8.899502 | 26.432444 | 8.969519 | 26.640402 | null | null |
rtx5090_training_seed22.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 109.106274 | 37,516.300725 | 0.000493 | 37,541.379271 | 104.940526 | 209.5 | 50.090943 | 268.946822 | 39.019062 | 12.896346 | 38.303484 | 13.230932 | 39.29724 | null | null |
rtx5090_training_seed22.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 198.680603 | 41,232.695682 | 0.000651 | 41,232.006926 | 115.257047 | 209.5 | 55.015297 | 268.946822 | 42.854958 | 20.89 | 62.045466 | 21.495808 | 63.844779 | null | null |
rtx5090_training_seed22.json | baseline_reused | NVIDIA GeForce RTX 5090 | GPU-c3733010-4951-8bd3-2692-36d9198c8d52 | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | null | oom | null | null | null | null | null | null | null | null | 209.5 | null | 268.946822 | null | 32.685051 | 97.077991 | 32.809943 | 97.448934 | null | CUDA out of memory. Tried to allocate 1000.00 MiB. GPU 0 has a total capacity of 31.36 GiB of which 247.88 MiB is free. Including non-PyTorch memory, this process has 31.11 GiB memory in use. Of the allocated memory 30.44 GiB is allocated by PyTorch, and 79.11 MiB is reserved by PyTorch but unallocated. If reserved but... |
h100_sxm_training_seed11_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 11 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 16 | 20 | 61.401377 | 33,350.282622 | 0.00629 | 33,354.300982 | 93.236263 | 989.5 | 9.422563 | 989.5 | 9.422563 | 8.949572 | 10.526741 | 9.032434 | 10.624206 | FLASH_ATTENTION | null |
h100_sxm_training_seed11_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 11 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 75.692318 | 53,998.58365 | 0.000599 | 54,113.813796 | 151.265942 | 989.5 | 15.287109 | 989.5 | 15.287109 | 12.946415 | 15.227943 | 13.293847 | 15.636601 | FLASH_ATTENTION | null |
h100_sxm_training_seed11_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 11 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 125.016914 | 65,532.76276 | 0.00045 | 65,527.1332 | 183.169931 | 989.5 | 18.511362 | 989.5 | 18.511362 | 20.940069 | 24.630307 | 21.537751 | 25.333317 | FLASH_ATTENTION | null |
h100_sxm_training_seed11_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 11 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 226.146065 | 72,439.383982 | 0.000584 | 72,448.751286 | 202.518134 | 989.5 | 20.466714 | 989.5 | 20.466714 | 36.927378 | 43.435035 | 38.094766 | 44.80815 | FLASH_ATTENTION | null |
h100_sxm_training_seed11_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 11 | 350m | 350M | 348,447,744 | 2,048 | 16 | 32,768 | complete | true | 11 | 20 | 422.757126 | 77,509.134354 | 0.000184 | 77,510.225129 | 216.666622 | 989.5 | 21.896576 | 989.5 | 21.896576 | 68.901995 | 81.044491 | 71.420609 | 84.006956 | FLASH_ATTENTION | null |
h100_sxm_training_seed11_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 11 | 350m | 350M | 348,447,744 | 2,048 | 32 | null | oom | null | null | null | null | null | null | null | null | 989.5 | null | 989.5 | null | 83.736987 | 98.493831 | 84.09999 | 98.920806 | null | CUDA out of memory. Tried to allocate 704.00 MiB. GPU 0 has a total capacity of 79.18 GiB of which 262.19 MiB is free. Including non-PyTorch memory, this process has 78.91 GiB memory in use. Of the allocated memory 77.99 GiB is allocated by PyTorch, and 206.19 MiB is reserved by PyTorch but unallocated. If reserved but... |
h100_sxm_training_seed22_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 22 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 26 | 20 | 62.902496 | 32,427.436607 | 0.015452 | 32,558.326286 | 91.011251 | 989.5 | 9.197701 | 989.5 | 9.197701 | 8.949572 | 10.526741 | 9.032434 | 10.624206 | FLASH_ATTENTION | null |
h100_sxm_training_seed22_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 76.027935 | 53,872.461221 | 0.000959 | 53,874.934239 | 150.598195 | 989.5 | 15.219626 | 989.5 | 15.219626 | 12.946415 | 15.227943 | 13.293847 | 15.636601 | FLASH_ATTENTION | null |
h100_sxm_training_seed22_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 125.351311 | 65,363.899136 | 0.000662 | 65,352.328207 | 182.681293 | 989.5 | 18.46198 | 989.5 | 18.46198 | 20.940069 | 24.630307 | 21.537751 | 25.333317 | FLASH_ATTENTION | null |
h100_sxm_training_seed22_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 226.512917 | 72,333.865269 | 0.000657 | 72,331.416011 | 202.190144 | 989.5 | 20.433567 | 989.5 | 20.433567 | 36.927378 | 43.435035 | 38.094766 | 44.80815 | FLASH_ATTENTION | null |
h100_sxm_training_seed22_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 22 | 350m | 350M | 348,447,744 | 2,048 | 16 | 32,768 | complete | true | 11 | 20 | 423.104874 | 77,407.650213 | 0.000201 | 77,446.519859 | 216.488544 | 989.5 | 21.87858 | 989.5 | 21.87858 | 68.901995 | 81.044491 | 71.420609 | 84.006956 | FLASH_ATTENTION | null |
h100_sxm_training_seed22_v2.json | baseline_reused | NVIDIA H100 80GB HBM3 | GPU-8f62317d-f779-de5a-419c-ecd52f14c564 | 22 | 350m | 350M | 348,447,744 | 2,048 | 32 | null | oom | null | null | null | null | null | null | null | null | 989.5 | null | 989.5 | null | 83.736987 | 98.493831 | 84.09999 | 98.920806 | null | CUDA out of memory. Tried to allocate 704.00 MiB. GPU 0 has a total capacity of 79.18 GiB of which 262.19 MiB is free. Including non-PyTorch memory, this process has 78.91 GiB memory in use. Of the allocated memory 77.99 GiB is allocated by PyTorch, and 206.19 MiB is reserved by PyTorch but unallocated. If reserved but... |
h200_training_seed11_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 11 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 63.520449 | 32,388.209986 | 0.019296 | 32,241.585858 | 90.125857 | 989.5 | 9.108222 | 989.5 | 9.108222 | 8.949572 | 5.961582 | 9.032434 | 6.016779 | FLASH_ATTENTION | null |
h200_training_seed11_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 11 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 71.832531 | 57,008.986304 | 0.000633 | 57,021.518585 | 159.393935 | 989.5 | 16.108533 | 989.5 | 16.108533 | 12.946415 | 8.624001 | 13.293847 | 8.855435 | FLASH_ATTENTION | null |
h200_training_seed11_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 11 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 115.485298 | 70,954.822947 | 0.000732 | 70,935.436205 | 198.28792 | 989.5 | 20.039204 | 989.5 | 20.039204 | 20.940069 | 13.948817 | 21.537751 | 14.346951 | FLASH_ATTENTION | null |
h200_training_seed11_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 11 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 204.711235 | 80,038.390096 | 0.000346 | 80,034.688845 | 223.72333 | 989.5 | 22.609735 | 989.5 | 22.609735 | 36.927378 | 24.598449 | 38.094766 | 25.376081 | FLASH_ATTENTION | null |
h200_training_seed11_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 11 | 350m | 350M | 348,447,744 | 2,048 | 16 | 32,768 | complete | true | 11 | 20 | 382.51535 | 85,670.749631 | 0.002186 | 85,664.536 | 239.460608 | 989.5 | 24.200162 | 989.5 | 24.200162 | 68.901995 | 45.897713 | 71.420609 | 47.575438 | FLASH_ATTENTION | null |
h200_training_seed11_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 11 | 350m | 350M | 348,447,744 | 2,048 | 32 | 65,536 | complete | true | 11 | 20 | 741.630951 | 88,343.307331 | 0.001344 | 88,367.401493 | 247.016007 | 989.5 | 24.96372 | 989.5 | 24.96372 | 132.851229 | 88.496241 | 137.774498 | 91.77578 | FLASH_ATTENTION | null |
h200_training_seed11_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 11 | 350m | 350M | 348,447,744 | 2,048 | 64 | null | oom | null | null | null | null | null | null | null | null | 989.5 | null | 989.5 | null | 148.101201 | 98.654711 | 148.860043 | 99.160199 | null | CUDA out of memory. Tried to allocate 1.38 GiB. GPU 0 has a total capacity of 139.81 GiB of which 1.01 GiB is free. Including non-PyTorch memory, this process has 138.79 GiB memory in use. Of the allocated memory 137.93 GiB is allocated by PyTorch, and 143.69 MiB is reserved by PyTorch but unallocated. If reserved but ... |
h200_training_seed22_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 22 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 64.234032 | 32,180.996256 | 0.012695 | 31,883.410499 | 89.124639 | 989.5 | 9.007038 | 989.5 | 9.007038 | 8.949572 | 5.961582 | 9.032434 | 6.016779 | FLASH_ATTENTION | null |
h200_training_seed22_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 71.30579 | 57,368.537533 | 0.001661 | 57,442.740667 | 160.57139 | 989.5 | 16.227528 | 989.5 | 16.227528 | 12.946415 | 8.624001 | 13.293847 | 8.855435 | FLASH_ATTENTION | null |
h200_training_seed22_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 114.963982 | 71,257.668031 | 0.000784 | 71,257.100563 | 199.187078 | 989.5 | 20.130074 | 989.5 | 20.130074 | 20.940069 | 13.948817 | 21.537751 | 14.346951 | FLASH_ATTENTION | null |
h200_training_seed22_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 204.14399 | 80,257.473467 | 0.000372 | 80,257.077542 | 224.344979 | 989.5 | 22.67256 | 989.5 | 22.67256 | 36.927378 | 24.598449 | 38.094766 | 25.376081 | FLASH_ATTENTION | null |
h200_training_seed22_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 22 | 350m | 350M | 348,447,744 | 2,048 | 16 | 32,768 | complete | true | 11 | 20 | 380.488678 | 86,091.074186 | 0.001168 | 86,120.828021 | 240.736094 | 989.5 | 24.329065 | 989.5 | 24.329065 | 68.901995 | 45.897713 | 71.420609 | 47.575438 | FLASH_ATTENTION | null |
h200_training_seed22_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 22 | 350m | 350M | 348,447,744 | 2,048 | 32 | 65,536 | complete | true | 11 | 20 | 741.72464 | 88,363.182911 | 0.001315 | 88,356.239601 | 246.984806 | 989.5 | 24.960567 | 989.5 | 24.960567 | 132.851229 | 88.496241 | 137.774498 | 91.77578 | FLASH_ATTENTION | null |
h200_training_seed22_v2.json | baseline_reused | NVIDIA H200 | GPU-b23aad41-8254-c13e-e269-0db430f83167 | 22 | 350m | 350M | 348,447,744 | 2,048 | 64 | null | oom | null | null | null | null | null | null | null | null | 989.5 | null | 989.5 | null | 148.101201 | 98.654711 | 148.860043 | 99.160199 | null | CUDA out of memory. Tried to allocate 1.38 GiB. GPU 0 has a total capacity of 139.81 GiB of which 1.01 GiB is free. Including non-PyTorch memory, this process has 138.79 GiB memory in use. Of the allocated memory 137.93 GiB is allocated by PyTorch, and 143.69 MiB is reserved by PyTorch but unallocated. If reserved but ... |
rtx6000_ada_training_seed11_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 11 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 95.738174 | 21,331.145108 | 0.010602 | 21,391.675912 | 59.796784 | 364.2 | 16.418667 | 451.433533 | 13.245977 | 8.899502 | 17.492245 | 8.969519 | 17.629866 | FLASH_ATTENTION | null |
rtx6000_ada_training_seed11_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 11 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 149.302689 | 27,496.959844 | 0.004483 | 27,434.201209 | 76.687633 | 364.2 | 21.056462 | 451.433533 | 16.98758 | 12.896346 | 25.348165 | 13.230932 | 26.005804 | FLASH_ATTENTION | null |
rtx6000_ada_training_seed11_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 11 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 298.339493 | 27,473.293798 | 0.002566 | 27,458.650959 | 76.755978 | 364.2 | 21.075227 | 451.433533 | 17.00272 | 20.89 | 41.059938 | 21.495808 | 42.250673 | FLASH_ATTENTION | null |
rtx6000_ada_training_seed11_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 11 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 633.509827 | 25,880.343028 | 0.003233 | 25,862.266551 | 72.293558 | 364.2 | 19.849961 | 451.433533 | 16.01422 | 36.877308 | 72.483486 | 38.052823 | 74.793996 | FLASH_ATTENTION | null |
rtx6000_ada_training_seed22_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 22 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 98.408192 | 20,875.714334 | 0.018992 | 20,811.275617 | 58.174373 | 364.2 | 15.973194 | 451.433533 | 12.886587 | 8.899502 | 17.492245 | 8.969519 | 17.629866 | FLASH_ATTENTION | null |
rtx6000_ada_training_seed22_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 149.961258 | 27,286.348185 | 0.005024 | 27,313.721267 | 76.350852 | 364.2 | 20.96399 | 451.433533 | 16.912977 | 12.896346 | 25.348165 | 13.230932 | 26.005804 | FLASH_ATTENTION | null |
rtx6000_ada_training_seed22_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 299.236435 | 27,370.787157 | 0.00206 | 27,376.345403 | 76.525907 | 364.2 | 21.012056 | 451.433533 | 16.951755 | 20.89 | 41.059938 | 21.495808 | 42.250673 | FLASH_ATTENTION | null |
rtx6000_ada_training_seed22_v2.json | baseline_reused | NVIDIA RTX 6000 Ada Generation | GPU-5b377adf-91ee-db42-9c14-0b8ba36df6b5 | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 633.111115 | 25,867.993963 | 0.003855 | 25,878.55374 | 72.339086 | 364.2 | 19.862462 | 451.433533 | 16.024305 | 36.877308 | 72.483486 | 38.052823 | 74.793996 | FLASH_ATTENTION | null |
a6000_training_seed11_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 11 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 160.565842 | 12,742.47702 | 0.003197 | 12,754.89219 | 35.654127 | 154.8 | 23.032382 | 180.6 | 19.742041 | 8.899502 | 17.438402 | 8.969519 | 17.575599 | FLASH_ATTENTION | null |
a6000_training_seed11_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 11 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 266.578659 | 15,366.299301 | 0.001199 | 15,365.070912 | 42.950437 | 154.8 | 27.74576 | 180.6 | 23.78208 | 12.896346 | 25.270139 | 13.230932 | 25.925755 | FLASH_ATTENTION | null |
a6000_training_seed11_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 11 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 473.321442 | 17,314.241494 | 0.000923 | 17,307.477074 | 48.380102 | 154.8 | 31.253296 | 180.6 | 26.788539 | 20.89 | 40.93355 | 21.495808 | 42.120619 | FLASH_ATTENTION | null |
a6000_training_seed11_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 11 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 880.804871 | 18,604.505985 | 0.000962 | 18,601.168711 | 51.996396 | 154.8 | 33.589403 | 180.6 | 28.790917 | 36.877308 | 72.260371 | 38.052823 | 74.563769 | FLASH_ATTENTION | null |
a6000_training_seed11_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 11 | 350m | 350M | 348,447,744 | 2,048 | 16 | null | oom | null | null | null | null | null | null | null | null | 154.8 | null | 180.6 | null | 50.538287 | 99.028794 | 50.671387 | 99.2896 | null | CUDA out of memory. Tried to allocate 128.00 MiB. GPU 0 has a total capacity of 47.53 GiB of which 68.25 MiB is free. Process 1348507 has 47.46 GiB memory in use. Of the allocated memory 47.00 GiB is allocated by PyTorch, and 130.93 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large... |
a6000_training_seed22_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 22 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 161.29744 | 12,702.76541 | 0.002619 | 12,697.039738 | 35.49241 | 154.8 | 22.927914 | 180.6 | 19.652497 | 8.899502 | 17.438402 | 8.969519 | 17.575599 | FLASH_ATTENTION | null |
a6000_training_seed22_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 268.032928 | 15,277.951733 | 0.001262 | 15,281.704466 | 42.7174 | 154.8 | 27.59522 | 180.6 | 23.653045 | 12.896346 | 25.270139 | 13.230932 | 25.925755 | FLASH_ATTENTION | null |
a6000_training_seed22_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 475.911697 | 17,212.869036 | 0.001298 | 17,213.277263 | 48.116782 | 154.8 | 31.083193 | 180.6 | 26.642737 | 20.89 | 40.93355 | 21.495808 | 42.120619 | FLASH_ATTENTION | null |
a6000_training_seed22_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 881.93576 | 18,574.509128 | 0.000519 | 18,577.316777 | 51.929722 | 154.8 | 33.546332 | 180.6 | 28.753999 | 36.877308 | 72.260371 | 38.052823 | 74.563769 | FLASH_ATTENTION | null |
a6000_training_seed22_v2.json | baseline_reused | NVIDIA RTX A6000 | GPU-18d70bd6-a015-e960-7fda-6a87d5e18b1f | 22 | 350m | 350M | 348,447,744 | 2,048 | 16 | null | oom | null | null | null | null | null | null | null | null | 154.8 | null | 180.6 | null | 50.538287 | 99.028794 | 50.671387 | 99.2896 | null | CUDA out of memory. Tried to allocate 128.00 MiB. GPU 0 has a total capacity of 47.53 GiB of which 68.25 MiB is free. Process 1380474 has 47.46 GiB memory in use. Of the allocated memory 47.00 GiB is allocated by PyTorch, and 130.93 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large... |
rtxpro6000_server_training_seed11_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 11 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 59.737488 | 34,287.5873 | 0.000603 | 34,283.329877 | 95.833205 | 468 | 20.47718 | 468 | 20.47718 | 8.899502 | 8.727231 | 8.969519 | 8.795893 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed11_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 11 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 89.900894 | 45,504.722155 | 0.00056 | 45,561.282099 | 127.358798 | 468 | 27.213418 | 468 | 27.213418 | 12.896346 | 12.646706 | 13.230932 | 12.974816 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed11_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 11 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 153.136406 | 53,492.229972 | 0.000279 | 53,494.790801 | 149.535569 | 468 | 31.952045 | 468 | 31.952045 | 20.89 | 20.485624 | 21.495808 | 21.079705 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed11_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 11 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 302.214905 | 54,209.127538 | 0.000145 | 54,213.077319 | 151.543416 | 468 | 32.381072 | 468 | 32.381072 | 36.877308 | 36.16346 | 38.052823 | 37.316219 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed11_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 11 | 350m | 350M | 348,447,744 | 2,048 | 16 | 32,768 | complete | true | 11 | 20 | 663.812103 | 49,353.89997 | 0.000195 | 49,363.366288 | 137.986876 | 468 | 29.484375 | 468 | 29.484375 | 68.851926 | 67.519131 | 71.420609 | 70.038091 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed11_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 11 | 350m | 350M | 348,447,744 | 2,048 | 32 | null | oom | null | null | null | null | null | null | null | null | 468 | null | 468 | null | 101.060531 | 99.104262 | 101.233721 | 99.2741 | null | CUDA out of memory. Tried to allocate 64.00 MiB. GPU 0 has a total capacity of 94.97 GiB of which 35.75 MiB is free. Including non-PyTorch memory, this process has 94.93 GiB memory in use. Of the allocated memory 94.12 GiB is allocated by PyTorch, and 165.17 MiB is reserved by PyTorch but unallocated. If reserved but u... |
rtxpro6000_server_training_seed22_merged_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 22 | 350m | 350M | 348,447,744 | 2,048 | 1 | 2,048 | complete | true | 11 | 20 | 59.891361 | 34,184.382876 | 0.001016 | 34,195.248826 | 95.586989 | 468 | 20.42457 | 468 | 20.42457 | 8.899502 | 8.727231 | 8.969519 | 8.795893 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed22_merged_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 22 | 350m | 350M | 348,447,744 | 2,048 | 2 | 4,096 | complete | true | 11 | 20 | 90.040977 | 45,489.437795 | 0.000545 | 45,490.399091 | 127.160656 | 468 | 27.17108 | 468 | 27.17108 | 12.896346 | 12.646706 | 13.230932 | 12.974816 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed22_merged_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 22 | 350m | 350M | 348,447,744 | 2,048 | 4 | 8,192 | complete | true | 11 | 20 | 153.200363 | 53,467.414979 | 0.000232 | 53,472.4581 | 149.473141 | 468 | 31.938705 | 468 | 31.938705 | 20.89 | 20.485624 | 21.495808 | 21.079705 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed22_merged_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 22 | 350m | 350M | 348,447,744 | 2,048 | 8 | 16,384 | complete | true | 11 | 20 | 302.34848 | 54,190.993742 | 0.000328 | 54,189.126361 | 151.476465 | 468 | 32.366766 | 468 | 32.366766 | 36.877308 | 36.16346 | 38.052823 | 37.316219 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed22_merged_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 22 | 350m | 350M | 348,447,744 | 2,048 | 16 | 32,768 | complete | true | 11 | 20 | 664.104218 | 49,342.165879 | 0.000212 | 49,341.653215 | 137.926181 | 468 | 29.471406 | 468 | 29.471406 | 68.851926 | 67.519131 | 71.420609 | 70.038091 | FLASH_ATTENTION | null |
rtxpro6000_server_training_seed22_merged_v2.json | baseline_reused | NVIDIA RTX PRO 6000 Blackwell Server Edition | GPU-0adc4b73-c849-be4e-7fc3-492d46abdd3e | 22 | 350m | 350M | 348,447,744 | 2,048 | 32 | null | oom | null | null | null | null | null | null | null | null | 468 | null | 468 | null | 101.060531 | 99.104262 | 101.233721 | 99.2741 | null | CUDA out of memory. Tried to allocate 64.00 MiB. GPU 0 has a total capacity of 94.97 GiB of which 35.75 MiB is free. Including non-PyTorch memory, this process has 94.93 GiB memory in use. Of the allocated memory 94.12 GiB is allocated by PyTorch, and 165.17 MiB is reserved by PyTorch but unallocated. If reserved but u... |
a100_pcie_context_frontier_seed11_v2.json | context_frontier | NVIDIA A100 80GB PCIe | GPU-2e75422d-0492-4288-c66f-44c400810994 | 11 | 350m | 350M | 348,447,744 | 4,096 | 4 | 16,384 | complete | true | 11 | 20 | 518.789032 | 31,576.891662 | 0.00085 | 31,581.23821 | 110.533469 | 312 | 35.427394 | 312 | 35.427394 | 36.885928 | 43.408365 | 38.038143 | 44.764323 | FLASH_ATTENTION | null |
a100_pcie_context_frontier_seed11_v2.json | context_frontier | NVIDIA A100 80GB PCIe | GPU-2e75422d-0492-4288-c66f-44c400810994 | 11 | 350m | 350M | 348,447,744 | 4,096 | 8 | 32,768 | complete | true | 11 | 20 | 994.44577 | 32,949.47541 | 0.001423 | 32,951.017521 | 115.327659 | 312 | 36.963993 | 312 | 36.963993 | 68.861826 | 81.038472 | 71.399637 | 84.025038 | FLASH_ATTENTION | null |
a100_pcie_context_frontier_seed11_v2.json | context_frontier | NVIDIA A100 80GB PCIe | GPU-2e75422d-0492-4288-c66f-44c400810994 | 11 | 350m | 350M | 348,447,744 | 4,096 | 16 | null | oom | null | null | null | null | null | null | null | null | 312 | null | 312 | null | 83.694257 | 98.493682 | 84.137738 | 99.015582 | null | CUDA out of memory. Tried to allocate 704.00 MiB. GPU 0 has a total capacity of 79.14 GiB of which 512.75 MiB is free. Process 764857 has 78.63 GiB memory in use. Of the allocated memory 77.95 GiB is allocated by PyTorch, and 182.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large... |
a100_pcie_context_frontier_seed22_v2.json | context_frontier | NVIDIA A100 80GB PCIe | GPU-2e75422d-0492-4288-c66f-44c400810994 | 22 | 350m | 350M | 348,447,744 | 4,096 | 4 | 16,384 | complete | true | 11 | 20 | 519.942657 | 31,511.513592 | 0.001539 | 31,511.167173 | 110.288222 | 312 | 35.348789 | 312 | 35.348789 | 36.885928 | 43.408365 | 38.038143 | 44.764323 | FLASH_ATTENTION | null |
a100_pcie_context_frontier_seed22_v2.json | context_frontier | NVIDIA A100 80GB PCIe | GPU-2e75422d-0492-4288-c66f-44c400810994 | 22 | 350m | 350M | 348,447,744 | 4,096 | 8 | 32,768 | complete | true | 11 | 20 | 995.761719 | 32,917.080986 | 0.001274 | 32,907.471118 | 115.175248 | 312 | 36.915143 | 312 | 36.915143 | 68.861826 | 81.038472 | 71.399637 | 84.025038 | FLASH_ATTENTION | null |
a100_pcie_context_frontier_seed22_v2.json | context_frontier | NVIDIA A100 80GB PCIe | GPU-2e75422d-0492-4288-c66f-44c400810994 | 22 | 350m | 350M | 348,447,744 | 4,096 | 16 | null | oom | null | null | null | null | null | null | null | null | 312 | null | 312 | null | 83.694257 | 98.493682 | 84.137738 | 99.015582 | null | CUDA out of memory. Tried to allocate 704.00 MiB. GPU 0 has a total capacity of 79.14 GiB of which 512.75 MiB is free. Process 852916 has 78.63 GiB memory in use. Of the allocated memory 77.95 GiB is allocated by PyTorch, and 182.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large... |
b200_context_frontier_seed11_v2.json | context_frontier | NVIDIA B200 | GPU-c4a7ec32-9030-147d-7e07-b6668d499a32 | 11 | 350m | 350M | 348,447,744 | 4,096 | 8 | 32,768 | complete | true | 11 | 20 | 347.215225 | 94,355.794539 | 0.00068 | 94,373.74176 | 330.305511 | 2,250 | 14.680245 | 2,250 | 14.680245 | 68.861826 | 35.958613 | 71.290585 | 37.226875 | FLASH_ATTENTION | null |
b200_context_frontier_seed11_v2.json | context_frontier | NVIDIA B200 | GPU-c4a7ec32-9030-147d-7e07-b6668d499a32 | 11 | 350m | 350M | 348,447,744 | 4,096 | 16 | 65,536 | complete | true | 11 | 20 | 651.912567 | 100,508.20838 | 0.000172 | 100,528.818286 | 351.84811 | 2,250 | 15.637694 | 2,250 | 15.637694 | 132.81362 | 69.353281 | 137.690612 | 71.899973 | FLASH_ATTENTION | null |
b200_context_frontier_seed11_v2.json | context_frontier | NVIDIA B200 | GPU-c4a7ec32-9030-147d-7e07-b6668d499a32 | 11 | 350m | 350M | 348,447,744 | 4,096 | 32 | null | oom | null | null | null | null | null | null | null | null | 2,250 | null | 2,250 | null | 190.422553 | 99.435803 | 190.551425 | 99.503098 | null | CUDA out of memory. Tried to allocate 256.00 MiB. GPU 0 has a total capacity of 178.35 GiB of which 155.81 MiB is free. Including non-PyTorch memory, this process has 178.19 GiB memory in use. Of the allocated memory 177.24 GiB is allocated by PyTorch, and 134.93 MiB is reserved by PyTorch but unallocated. If reserved ... |
b200_context_frontier_seed22_v2.json | context_frontier | NVIDIA B200 | GPU-c4a7ec32-9030-147d-7e07-b6668d499a32 | 22 | 350m | 350M | 348,447,744 | 4,096 | 8 | 32,768 | complete | true | 11 | 20 | 348.208771 | 93,934.887514 | 0.002369 | 94,104.46477 | 329.363049 | 2,250 | 14.638358 | 2,250 | 14.638358 | 68.861826 | 35.958613 | 71.290585 | 37.226875 | FLASH_ATTENTION | null |
b200_context_frontier_seed22_v2.json | context_frontier | NVIDIA B200 | GPU-c4a7ec32-9030-147d-7e07-b6668d499a32 | 22 | 350m | 350M | 348,447,744 | 4,096 | 16 | 65,536 | complete | true | 11 | 20 | 652.359375 | 100,389.157993 | 0.000772 | 100,459.965031 | 351.607126 | 2,250 | 15.626983 | 2,250 | 15.626983 | 132.81362 | 69.353281 | 137.690612 | 71.899973 | FLASH_ATTENTION | null |
b200_context_frontier_seed22_v2.json | context_frontier | NVIDIA B200 | GPU-c4a7ec32-9030-147d-7e07-b6668d499a32 | 22 | 350m | 350M | 348,447,744 | 4,096 | 32 | null | oom | null | null | null | null | null | null | null | null | 2,250 | null | 2,250 | null | 190.422553 | 99.435803 | 190.551425 | 99.503098 | null | CUDA out of memory. Tried to allocate 256.00 MiB. GPU 0 has a total capacity of 178.35 GiB of which 155.81 MiB is free. Including non-PyTorch memory, this process has 178.19 GiB memory in use. Of the allocated memory 177.24 GiB is allocated by PyTorch, and 134.93 MiB is reserved by PyTorch but unallocated. If reserved ... |
b300_context_frontier_seed11_v2.json | context_frontier | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 11 | 350m | 350M | 348,447,744 | 4,096 | 16 | 65,536 | complete | true | 11 | 20 | 649.614685 | 100,857.646321 | 0.000302 | 100,884.418883 | 353.092703 | 2,250 | 15.693009 | 2,250 | 15.693009 | 132.81362 | 46.207511 | 137.652863 | 47.891144 | FLASH_ATTENTION | null |
b300_context_frontier_seed11_v2.json | context_frontier | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 11 | 350m | 350M | 348,447,744 | 4,096 | 32 | 131,072 | complete | true | 11 | 20 | 1,246.777405 | 105,123.088668 | 0.000186 | 105,128.629615 | 367.947324 | 2,250 | 16.353214 | 2,250 | 16.353214 | 260.717208 | 90.70676 | 270.28095 | 94.034105 | FLASH_ATTENTION | null |
b300_context_frontier_seed11_v2.json | context_frontier | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 11 | 350m | 350M | 348,447,744 | 4,096 | 64 | null | oom | null | null | null | null | null | null | null | null | 2,250 | null | 2,250 | null | 285.990779 | 99.49975 | 286.517101 | 99.682864 | null | CUDA out of memory. Tried to allocate 512.00 MiB. GPU 0 has a total capacity of 267.69 GiB of which 435.62 MiB is free. Including non-PyTorch memory, this process has 267.25 GiB memory in use. Of the allocated memory 266.35 GiB is allocated by PyTorch, and 81.94 MiB is reserved by PyTorch but unallocated. If reserved b... |
b300_context_frontier_seed22_v2.json | context_frontier | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 4,096 | 16 | 65,536 | complete | true | 11 | 20 | 648.799744 | 100,991.414423 | 0.000461 | 101,011.137321 | 353.536214 | 2,250 | 15.712721 | 2,250 | 15.712721 | 132.81362 | 46.207511 | 137.652863 | 47.891144 | FLASH_ATTENTION | null |
b300_context_frontier_seed22_v2.json | context_frontier | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 4,096 | 32 | 131,072 | complete | true | 11 | 20 | 1,246.151611 | 105,183.22889 | 0.000084 | 105,181.423198 | 368.1321 | 2,250 | 16.361427 | 2,250 | 16.361427 | 260.717208 | 90.70676 | 270.28095 | 94.034105 | FLASH_ATTENTION | null |
b300_context_frontier_seed22_v2.json | context_frontier | NVIDIA B300 SXM6 AC | GPU-589e52a7-94b4-3cdf-33cc-048fbf864c10 | 22 | 350m | 350M | 348,447,744 | 4,096 | 64 | null | oom | null | null | null | null | null | null | null | null | 2,250 | null | 2,250 | null | 285.990779 | 99.49975 | 286.517101 | 99.682864 | null | CUDA out of memory. Tried to allocate 512.00 MiB. GPU 0 has a total capacity of 267.69 GiB of which 435.62 MiB is free. Including non-PyTorch memory, this process has 267.25 GiB memory in use. Of the allocated memory 266.35 GiB is allocated by PyTorch, and 81.94 MiB is reserved by PyTorch but unallocated. If reserved b... |
rtx4090_context_frontier_seed11_v2.json | context_frontier | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 11 | 350m | 350M | 348,447,744 | 4,096 | 1 | 4,096 | complete | true | 11 | 20 | 155.843872 | 26,251.992905 | 0.001459 | 26,282.714524 | 91.988781 | 165.2 | 55.683281 | 205.516667 | 44.759767 | 12.903973 | 51.082493 | 12.952011 | 51.272658 | FLASH_ATTENTION | null |
rtx4090_context_frontier_seed11_v2.json | context_frontier | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 11 | 350m | 350M | 348,447,744 | 4,096 | 2 | 8,192 | complete | true | 11 | 20 | 305.162827 | 26,846.626787 | 0.006423 | 26,844.685157 | 93.955663 | 165.2 | 56.873888 | 205.516667 | 45.716809 | 20.89798 | 82.72808 | 21.506294 | 85.13619 | FLASH_ATTENTION | null |
rtx4090_context_frontier_seed11_v2.json | context_frontier | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 11 | 350m | 350M | 348,447,744 | 4,096 | 4 | null | oom | null | null | null | null | null | null | null | null | 165.2 | null | 205.516667 | null | 24.635704 | 97.524475 | 24.708645 | 97.813222 | null | CUDA out of memory. Tried to allocate 88.00 MiB. GPU 0 has a total capacity of 23.53 GiB of which 47.69 MiB is free. Including non-PyTorch memory, this process has 23.47 GiB memory in use. Of the allocated memory 22.94 GiB is allocated by PyTorch, and 69.56 MiB is reserved by PyTorch but unallocated. If reserved but un... |
rtx4090_context_frontier_seed22_v2.json | context_frontier | NVIDIA GeForce RTX 4090 | GPU-5447a6b8-ccd6-9d49-4872-492ff5116ee3 | 22 | 350m | 350M | 348,447,744 | 4,096 | 1 | 4,096 | complete | true | 11 | 20 | 156.05661 | 26,246.988558 | 0.00088 | 26,246.885647 | 91.863381 | 165.2 | 55.607373 | 205.516667 | 44.69875 | 12.903973 | 51.082493 | 12.952011 | 51.272658 | FLASH_ATTENTION | null |
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