Update H200 CUDA flops

[davertor]

Description & Motivation

Calculation of available flops during ThroughputMonitor callback in H200 is not supported

Pitch

When looking at _CUDA_FLOPS dict, H200 data has not been added. Official data can be extracted from here https://nvdam.widen.net/s/nb5zzzsjdf/hpc-datasheet-sc23-h200-datasheet-3002446

_CUDA_FLOPS: dict[str, dict[Union[str, torch.dtype], float]] = { # Hopper # source: https://resources.nvidia.com/en-us-tensor-core "h100 nvl": { torch.float64: 67e12, torch.float32: 133.8e12, "tfloat32": 989.4e12, torch.bfloat16: 1978.8e12, torch.float16: 1978.8e12, torch.int8: 3957.8e12, }, "h100 sxm": { torch.float64: 33.5e12, torch.float32: 66.9e12, "tfloat32": 494.7e12, torch.bfloat16: 989.4e12, torch.float16: 989.4e12, torch.int8: 1978.9e12, }, "h100 pcie": { torch.float64: 25.6e12, torch.float32: 51.2e12, "tfloat32": 378e12, torch.bfloat16: 756e12, torch.float16: 756e12, torch.int8: 1513e12, }, # Ada # source: https://images.nvidia.com/aem-dam/Solutions/Data-Center/l4/nvidia-ada-gpu-architecture-whitepaper-v2.1.pdf "rtx 4090": { torch.float32: 82.6e12, "tfloat32": 82.6e12, torch.bfloat16: 82.6e12, torch.float16: 82.6e12, torch.int8: 660.6e12, "int4": 1321.2e12, }, "rtx 4080": { torch.float32: 48.7e12, "tfloat32": 48.7e12, torch.bfloat16: 48.7e12, torch.float16: 48.7e12, torch.int8: 389.9e12, "int4": 779.8e12, }, "rtx 4080 super": { torch.float32: 52.2e12, "tfloat32": 52.2e12, torch.bfloat16: 52.2e12, torch.float16: 52.2e12, torch.int8: 417.6e12, "int4": 835.2e12, }, "l4": { torch.float32: 30.3e12, "tfloat32": 60e12, torch.bfloat16: 121e12, torch.float16: 121e12, torch.int8: 242e12, "int4": 484e12, }, "l40": { torch.float32: 90.5e12, "tfloat32": 90.5e12, torch.bfloat16: 181e12, torch.float16: 181e12, torch.int8: 362e12, "int4": 724e12, }, # Ampere # source: https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/a100/pdf/nvidia-a100-datasheet-us-nvidia-1758950-r4-web.pdf # sxm and pcie have same flop counts "a100": { torch.float64: 9.7e12, torch.float32: 19.5e12, "tfloat32": 156e12, torch.bfloat16: 312e12, torch.float16: 312e12, torch.int8: 624e12, }, "a6000": { torch.float32: 38.7e12, "tfloat32": 77.4e12, torch.bfloat16: 38.7e12, torch.float16: 38.7e12, torch.int8: 309.7e12, "int4": 619.3e12, }, "a40": { torch.float32: 37.4e12, "tfloat32": 74.8e12, torch.bfloat16: 37.4e12, torch.float16: 37.4e12, torch.int8: 299.3e12, "int4": 598.7e12, }, # source: https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/a10/pdf/a10-datasheet.pdf "a10g": { torch.float32: 31.2e12, "tfloat32": 62.5e12, torch.bfloat16: 125e12, torch.float16: 125e12, torch.int8: 250e12, "int4": 500e12, }, "rtx 3090 ti": { torch.float32: 40e12, "tfloat32": 40e12, torch.bfloat16: 40e12, torch.float16: 40e12, torch.int8: 320e12, "int4": 640e12, }, "rtx 3090": { torch.float32: 35.6e12, "tfloat32": 35.6e12, torch.bfloat16: 35.6e12, torch.float16: 35.6e12, torch.int8: 284e12, "int4": 568e12, }, "rtx 3080 ti": { torch.float32: 34.1e12, "tfloat32": 34.1e12, torch.bfloat16: 34.1e12, torch.float16: 34.1e12, torch.int8: 272.8e12, "int4": 546.6e12, }, "rtx 3080": { torch.float32: 29.8e12, "tfloat32": 29.8e12, torch.bfloat16: 29.8e12, torch.float16: 29.8e12, torch.int8: 238e12, "int4": 476e12, }, "rtx 3070": { torch.float32: 20.3e12, "tfloat32": 20.3e12, torch.bfloat16: 20.3e12, torch.float16: 20.3e12, torch.int8: 162.6e12, "int4": 325.2e12, }, # Turing # source: https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/tesla-t4/t4-tensor-core-datasheet-951643.pdf # sxm and pcie have same flop counts "t4": { torch.float32: 8.1e12, torch.float16: 65e12, torch.int8: 130e12, "int4": 260e12, }, # https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/quadro-rtx-5000-data-sheet-us-nvidia-704120-r4-web.pdf "quadro rtx 5000": { torch.float32: 11.2e12, torch.float16: 89.2e12, }, "rtx 2080 super": { torch.float32: 11.2e12, torch.float16: 22.3e12, torch.int8: 178.4e12, "int4": 356.8e12, }, "rtx 2080 ti": { torch.float32: 14.2e12, torch.float16: 28.5e12, torch.int8: 227.7e12, "int4": 455.4e12, }, "rtx 2080": { torch.float32: 10.6e12, torch.float16: 21.2e12, torch.int8: 169.6e12, "int4": 339.1e12, }, # https://www.nvidia.com/content/PDF/nvidia-ampere-ga-102-gpu-architecture-whitepaper-v2.pdf "rtx 2070 super": { torch.float32: 9.1e12, torch.float16: 18.1e12, torch.int8: 145e12, "int4": 290e12, }, "titan rtx": { torch.float32: 16.3e12, torch.float16: 32.6e12, torch.int8: 261e12, "int4": 522e12, }, # Volta # source: https://images.nvidia.com/content/technologies/volta/pdf/volta-v100-datasheet-update-us-1165301-r5.pdf "v100 sxm": { torch.float64: 7.8e12, torch.float32: 15.7e12, torch.float16: 125e12, }, "v100 pcie": { torch.float64: 7e12, torch.float32: 14e12, torch.float16: 112e12, }, "v100s pcie": { torch.float64: 8.2e12, torch.float32: 16.4e12, torch.float16: 130e12, }, }

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