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Release Date: August 06, 2019

Summary

High Performance Computing (HPC) is the use of parallel-processing techniques to solve complex computational problems. HPC systems have the ability to deliver sustained performance through the concurrent use of distributed computing resources,and they are typically used for solving advanced scientific and engineering problems, such as computational fluid dynamics, bioinformatics, molecular dynamics, weather modeling and deep learning with neural networks.

Due to their extreme demand on performance, HPC workloads often have much more intensive resource requirements than those workloads found in the typical enterprise. For example, HPC commonly leverages hardware accelerators, such as GPU and FPGA for compute as well as RDMA interconnects, which require special vSphere configurations.

This toolkit is intended to facilitate managing the lifecycle of these special configurations by leveraging vSphere APIs. It also includes features that help vSphere administrators perform some common vSphere tasks that are related to creating such high-performing environments, such as VM cloning, setting Latency Sensitivity, and sizing vCPUs, memory, etc.

Feature Highlights:

  • Configure PCIe devices in DirectPath I/O mode, such as GPGPU, FPGA and RDMA interconnects
  • Configure NVIDIA vGPU
  • Configure RDMA SR-IOV (Single Root I/O Virtualization)
  • Configure  PVRDMA (Paravirtualized RDMA)
  • Easy creation and  destruction of virtual HPC clusters using cluster configuration files
  • Perform common vSphere tasks, such as cloning VMs, configuring vCPUs, memory, reservations, shares, Latency Sensitivity, Distributed Virtual Switch/Standard Virtual Switch, network adapters and network configurations
Requirements
  • OS for using this toolkit: Linux or Mac
  • vSphere >=6.5
  • Python >=3
Instructions
Please read the instructions from the ReadME.md
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