计算能力适用范围(Compute Capability):9.0 英伟达在2022年3月下旬发布了采用全新Hopper架构的H100,拥有NVIDIA当前最强的GPU规格。英伟达H100核心架构与上一代Ampere相似,数学运算部分布置在144组CUDA上,最高可拥有18432个FP32(单精度)、9216个FP64(双精度)CUDA核心,辅以576个第四代Tensor核心。 NVIDIA在2022年5月初曝...
SM90 orSM_90, compute_90– NVIDIA H100 (GH100), NVIDIAH200 SM90a orSM_90a, compute_90a– (适用于 PTX ISA 8.0 版)- 为 wgmma 和 setmaxnreg 等功能添加了加速功能。英伟达™(NVIDIA®)CUTLASS 需要此功能。 Blackwell 架构 (CUDA 12 至今) SM95 orSM_95, compute_95– NVIDIA B100 (GB100...
H100 FP8 Tensor Core 的吞吐量是 A100 FP16 Tensor Core 的 6 倍 图8 。 H100 TF32 、 FP64 和 INT8 张量核的吞吐量都是 A100 的 6 倍 表2 显示了多种数据类型的 H100 数学加速比超过 A100 。 (measurements in TFLOPS)A100A100SparseH100 SXM51H100 SXM51SparseH100 SXM51Speedup vs A100 FP8 Tens...
The H100’s dedicated Transformer Engine optimizes the training and inference of Transformer models, which are fundamental to many modern AI applications, including natural language processing and computer vision. This capability helps accelerate research and deployment of AI solutions across various fields...
计算能力适用范围(Compute Capability):9.0 英伟达在2022年3月下旬发布了采用全新Hopper架构的H100,拥有NVIDIA当前最强的GPU规格。英伟达H100核心架构与上一代Ampere相似,数学运算部分布置在144组CUDA上,最高可拥有18432个FP32(单精度)、9216个FP64(双精度)CUDA核心,辅以576个第四代Tensor核心。 NVIDIA在2022年5月初曝...
The NVIDIA H100 GPU based on compute capability 9.0 increases the maximum capacity of the combined L1 cache, texture cache, and shared memory to 256 KB, from 192 KB in NVIDIA Ampere Architecture, an increase of 33%. In the NVIDIA Hopper GPU architecture, the portion of the L1 cache dedicat...
SM90 orSM_90, compute_90– NVIDIA H100 (GH100) SamplenvccgencodeandarchFlags According to NVIDIA: Thearch=clause of the-gencode=command-line option tonvccspecifies the front-end compilation target and must always be a PTX version. Thecode=clause specifies the back-end compilation target and ...
H100 is bringing massive amounts of compute to data centers. To fully utilize that compute performance, the NVIDIA H100 PCIe utilizes HBM2e memory with a class-leading 2 terabytes per second (TB/sec) of memory bandwidth, a 50 percent increase over the previous generation. In addition to 80 ...
H100 FP16 Latency 16 A100 FP16 Latency 16Non-optimized configuration Any NVIDIA GPU with sufficient GPU memory or multiple, homogeneous NVIDIA GPUs with sufficient aggregate memory, compute capability > 7.0 (8.0 for bfloat16), and at least one GPU with 95% or greater free memory.Previous...
NVIDIA Hopper 应用调优指南说明书 DA-11076-001_v11.8 | October 2022Tuning CUDA Applications for Hopper Application Note