H800

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Terms

  • SXM: Server PCI Express Module, a high bandwidth socket solution for connecting Nvidia Compute Accelerators to a system
  • NVL: NVLink is a wire-based serial multi-lane near-range communications link developed by Nvidia. Unlike PCI Express, a device can consist of multiple NVLinks, and devices use mesh networking to communicate instead of a central hub.
  • PCIe: PCI Express (Peripheral Component Interconnect Express), officially abbreviated as PCIe or PCI-e,[1] is a high-speed serial computer expansion bus standard

from Wikipedia

H800 vs H100

  1. https://resources.nvidia.com/en-us-tensor-core/nvidia-tensor-core-gpu-datasheet

  2. NVIDIA H100 Tensor Core GPU

  3. H800 没找到 NVIDIA 官网 Specification, 只能从代理商和一些B站UP主看到的数据

H800 SXM H100 SXM
FP64 1 teraFLOPS 34 teraFLOPS
FP64 Tensor Core 1 teraFLOPS 67 teraFLOPS
FP32 67 teraFLOPS 67 teraFLOPS
TF32 Tensor Core 989 teraFLOPS 989 teraFLOPS
BFLOAT16 Tensor Core 1,979 teraFLOPS 1,979 teraFLOPS
FP16 Tensor Core 1,979 teraFLOPS 1,979 teraFLOPS
FP8 Tensor Core 3,958 teraFLOPS 3,958 teraFLOPS
INT8 Tensor Core 3,958 TOPS 3,958 TOPS
GPU memory 80GB 80GB
GPU memory bandwidth 3.35TB/s 3.35TB/s
Interconnect NVLink 400GB/s PCIe Gen5: 128GB/s NVLink 900GB/s PCIe Gen5: 128GB/s
  • H800 FP64 算力限制

Driver

https://resources.nvidia.com/en-us-tensor-core/gtc22-whitepaper-hopper

https://www.nvidia.com/content/dam/en-zz/Solutions/gtcs22/data-center/h100/PB-11133-001_v01.pdf

Software Specifications

Specification Description
Driver support Linux: R520 or later

CUDA

https://docs.nvidia.com/datacenter/tesla/drivers/index.html#cuda-arch-matrix

Architecture CUDA Capabilities First CUDA Toolkit Support
Hopper 9.0 CUDA 11.8
CUDA 12.0

TensorFlow

https://www.tensorflow.org/install/source#tested_build_configurations

Version Python version Compiler Build tools cuDNN CUDA
tensorflow-2.15.0 3.9-3.11 Clang 16.0.0 Bazel 6.1.0 8.8 12.2
tensorflow-2.14.0 3.9-3.11 Clang 16.0.0 Bazel 6.1.0 8.7 11.8
tensorflow-2.13.0 3.8-3.11 Clang 16.0.0 Bazel 5.3.0 8.6 11.8
tensorflow-2.12.0 3.8-3.11 GCC 9.3.1 Bazel 5.3.0 8.6 11.8
tensorflow-2.11.0 3.7-3.10 GCC 9.3.1 Bazel 5.3.0 8.1 11.2
tensorflow-2.6.0 3.6-3.9 GCC 7.3.1 Bazel 3.7.2 8.1 11.2

candidates on H800

  • >= tensorflow-2.12.0

docker images

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docker pull tensorflow/tensorflow:2.14.0-gpu
docker pull tensorflow/tensorflow:2.13.0-gpu
docker pull tensorflow/tensorflow:2.12.0-gpu

PyTorch

https://pytorch.org/get-started/previous-versions/

Version CUDA
v1.13.1 11.6, 11.7
v2.0.0 11.7, 11.8
v2.0.1 11.7, 11.8
v2.1.0 11.8, 12.1
v2.1.1 11.8, 12.1

candidates on H800

  • >= v2.0.0, with cuda 11.8 support

docker images

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docker pull pytorch/pytorch:2.1.0-cuda11.8-cudnn8-devel
docker pull pytorch/pytorch:2.1.0-cuda11.8-cudnn8-runtime

docker pull pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel
docker pull pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime