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科学领域:

  • 高性能计算 (HPC) 是一种高性能计算.
  • 在 GPU 加速加速.
  • 臂架构的架构手臂架构.

背景情况:

  • 新型GPU加速臂测试台系统正在为HPC出现.
  • 评估这些系统需要对科学应用进行移植,验证和基准测试.

研究的目的:

  • 评估基于Arm的GPU系统对HPC的准备情况.
  • 评估开发人员在这些平台上部署科学工作负载的努力.

主要方法:

  • 十个团队移植,验证和对比HPC应用程序.
  • 应用程序使用各种编程语言和GPU模型 (CUDA,OpenACC,OpenMP卸载).
  • 在一个八个系统的NVIDIA Arm HPC开发者套件测试台上进行了测试,配备了Ampere CPU和NVIDIA GPU,通过InfiniBand连接.

主要成果:

  • 基于Arm的GPU测试台证明了对HPC工作负载的准备.
  • 软件和工具已经足够成熟,可以进行大规模的生产部署.
  • 案例研究证实了Arm生态系统对科学计算的可行性.

结论:

  • 基于ARM的GPU加速的HPC系统是可行的生产.
  • 目前的软件和工具链成熟度支持广泛采用.
  • 基于Arm架构的未来HPC系统是有希望的.