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Scaling HPC and ML with GPUDirect RDMA on vSphere 6.7 (Part 1 of 2)

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Introduction High Performance Computing (HPC) and Machine Learning (ML) workloads are extremely resource intensive, often relying on hardware acceleration to achieve the performance necessary to solve large, complex problems in a timely way. Interconnect acceleration – special hardware that delivers extremely high bandwidth and low latency, and compute acceleration – often delivered through exploitation of Read more...

Virtualized High Performance Computing (HPC) Reference Architecture (Part 2 of 2)

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In part 1 of this series we looked at traditional HPC and introduced  virtualized HPC components. Part 2 will look at the design and show sample virtual reference architectures for  HPC workloads. vSphere Clusters: High Performance Computing workloads have management and compute components. Most VMware environments have a separate management cluster that should be leveraged. Read more...

New Architectures for Apache Spark™ and Big Data

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Key Trends in Big Data Infrastructure: Some of the key trends in big data infrastructure over the past couple of years are: • Decoupling of Compute and Storage Clusters • Separate compute virtual machines from storage VMs • Data is processed and scaled independently of compute • Dynamic Scaling of compute nodes used for analysis Read more...