Supporting High Performance Molecular Dynamics in Virtualized Clusters using IOMMU, SR-IOV, and GPUDirect

A. Younge, J. Walters, S. Crago, Geoffrey Fox
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引用次数: 12

Abstract

Cloud Infrastructure-as-a-Service paradigms have recently shown their utility for a vast array of computational problems, ranging from advanced web service architectures to high throughput computing. However, many scientific computing applications have been slow to adapt to virtualized cloud frameworks. This is due to performance impacts of virtualization technologies, coupled with the lack of advanced hardware support necessary for running many high performance scientific applications at scale. By using KVM virtual machines that leverage both Nvidia GPUs and InfiniBand, we show that molecular dynamics simulations with LAMMPS and HOOMD run at near-native speeds. This experiment also illustrates how virtualized environments can support the latest parallel computing paradigms, including both MPI+CUDA and new GPUDirect RDMA functionality. Specific findings show initial promise in scaling of such applications to larger production deployments targeting large scale computational workloads.
使用IOMMU、SR-IOV和GPUDirect支持虚拟化集群中的高性能分子动力学
云基础设施即服务范式最近在大量计算问题(从高级web服务体系结构到高吞吐量计算)中显示了它们的实用性。然而,许多科学计算应用程序在适应虚拟化云框架方面进展缓慢。这是由于虚拟化技术对性能的影响,加上缺乏大规模运行许多高性能科学应用程序所需的高级硬件支持。通过使用利用Nvidia gpu和InfiniBand的KVM虚拟机,我们展示了LAMMPS和HOOMD的分子动力学模拟以接近本机的速度运行。这个实验还说明了虚拟化环境如何支持最新的并行计算范式,包括MPI+CUDA和新的GPUDirect RDMA功能。具体的研究结果显示,将此类应用程序扩展到针对大规模计算工作负载的更大的生产部署中,初步有望实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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