NVIDIA H100 Tensor Core GPU securely accelerates workloads from Enterprise to Exascale HPC and Trillion Parameter AI.
2022年,Nvidia 发布的最新一代高性能GPU架构:H100。H100 TensorCore中引入了一种新的浮点类型FP8. 相较于FP16/BF16, FP8能取得到2x的性能提升, 4096 MAC/cycle的水平. 无独有偶,2021年10月,Tesla披露了关于Dojo的一些细节。 其中最引人关注的是Dojo White Paper 提到的一种新的可配置的浮点格式:CFloat8。
(a) A100编程模型 (b)H100 Thread Block Cluster 编程模型 (c)H100 编程模型示例 四、互联 上:NVL32通过 NVLink 和 NVSwitch 互联 下:通过 PCIe 互联 五、参考文献 NVIDIA Grace Hopper Superchip Architecture Whitepaper NVIDIA Hopper Architecture In-Depth | NVIDIA Technical Blog hc34.hotchips.org/asset...
A high-level overview of NVIDIA H100, new H100-based DGX, DGX SuperPOD, and HGX systems, and a H100-based Converged Accelerator. This is followed by a deep dive into the H100 hardware architecture, efficiency improvements, and new programming features.
[1]使用32個HPE Cray EX 2500節點並搭載128個NVIDIA H100 GPU,以97%的擴展效能成功在3分鐘以內對一個包含1,000萬標記的語料庫進行70億參數的Llama 2模型微調。在擴展運行間,模型微調代碼和訓練參數並未最佳化。 2 標準 AI 基準測試,BERT 和 Mask R-CNN,使用開箱即用、未經調整的系統,包含HPE Cray EX2500 ...
[1]使用32個HPE Cray EX 2500節點並搭載128個NVIDIA H100 GPU,以97%的擴展效能成功在3分鐘以內對一個包含1,000萬標記的語料庫進行70億參數的Llama 2模型微調。在擴展運行間,模型微調代碼和訓練參數並未最佳化。 2 標準 AI 基準測試,BERT 和 Mask R-CNN,使用開箱即用、未經調整的系統,包含HPE Cray EX2500 ...
For more information about the speedups that Grace Hopper achieves over the most powerful PCIe-based accelerated platforms using NVIDIA Hopper H100 GPUs, see the NVIDIA Grace Hopper Superchip Architecture whitepaper. Performance and productivity for strong-scaling HPC and giant AI workloads The NVIDIA ...
The ThinkSystem SR680a V3 is an air cooled, two-socket system, featuring the world’s most powerful GPUs for supercharging AI and HPC workloads with time-to-market support for NVIDIA HGX AI supercomputing platform, including H100, H200 and the all-new B200 architectures. ...
In fact, Nvidia added SM-SM on-chip transmission channels to the H100 to reuse data between SMs and reduce the number of accesses, but this usually requires programmers to do it manually, which also makes performance optimization more difficult. In addition, the entire GPU software stack was ...
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