New White Paper: Optimize Virtualized Deep Learning Performance with New Intel Architectures

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By Dave Jaffe, VMware Performance Engineering and Padma Apparao, Intel – VMware Center of Excellence A new white paper is available showing the advantages of running deep learning image classification on the 2nd Generation Intel Xeon Scalable processor compared to previous Intel processors, and to show the performance benefits of running on the VMware vSphere Read more...

Introducing VMmark ML

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VMmark has been the go-to virtualization benchmark for over 12 years. It’s been used by partners, customers, and internally in a wide variety of technical applications. VMmark1, released in 2007, was the de-facto virtualization consolidation benchmark in a time when the overhead and feasibility of virtualization was still largely in question. In 2010, as server Read more...

Sharing GPU for Machine Learning/Deep Learning on VMware vSphere with NVIDIA GRID: Why is it needed? And How to share GPU?

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By Lan Vu, Uday Kurkure, and Hari Sivaraman  Data scientists may use GPUs on vSphere that are dedicated to use by one virtual machine only for their modeling work, if they need to. Certain heavier machine learning workloads may well require that dedicated approach. However, there are also many ML workloads and user types that do not use Read more...
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VMware Speedily Resolves Customer Issues in vSAN Performance Using AI

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We in VMware’s Performance team create and maintain various tools to help troubleshoot customer issues—of these, there is a new one that allows us to more quickly determine storage problems from vast log data using artificial intelligence. What used to take us days, now takes seconds. PerfPsychic analyzes storage system performance and finds performance bottlenecks Read more...

New white paper: Big Data performance on VMware Cloud on AWS: Spark machine learning and IoT analytics performance on-premises and in the cloud

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By Dave Jaffe A new white paper is available comparing Spark machine learning performance on an 8-server on-premises cluster vs. a similarly configured VMware Cloud on AWS cluster. Here is what the VMware Cloud on AWS cluster looked like: Three standard analytic programs from the Spark machine learning library (MLlib), K-means clustering, Logistic Regression classification, Read more...

Performance Comparison of Containerized Machine Learning Applications Running Natively with Nvidia vGPUs vs. in a VM – Episode 4

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This article is by Hari Sivaraman, Uday Kurkure, and Lan Vu from the Performance Engineering team at VMware. Performance Comparison of Containerized Machine Learning Applications Docker containers [6] are rapidly becoming a popular environment in which to run different applications, including those in machine learning [1, 2, 3]. NVIDIA supports Docker containers with their own Docker engine Read more...

Episode 3: Performance Comparison of Native GPU to Virtualized GPU and Scalability of Virtualized GPUs for Machine Learning

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In our third episode of machine learning performance with vSphere 6.x, we look at the virtual GPU vs. the physical GPU. In addition, we extend the performance results of machine learning workloads using VMware DirectPath I/O (passthrough) vs. NVIDIA GRID vGPU that have been partially addressed in previous episodes: Episode 1: Performance Results of Machine Read more...

Machine Learning on vSphere 6 with Nvidia GPUs – Episode 2

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by Hari Sivaraman, Uday Kurkure, and Lan Vu In a previous blog [1], we looked at how machine learning workloads (MNIST and CIFAR-10) using TensorFlow running in vSphere 6 VMs in an NVIDIA GRID configuration reduced the training time from hours to minutes when compared to the same system running no virtual GPUs. Here, we extend our study Read more...

Machine Learning on VMware vSphere 6 with NVIDIA GPUs

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by Uday Kurkure, Lan Vu, and Hari Sivaraman Machine learning is an exciting area of technology that allows computers to behave without being explicitly programmed, that is, in the way a person might learn. This tech is increasingly applied in many areas like health science, finance, and intelligent systems, among others. In recent years, the Read more...