In Part 1 we described the solution components and the test cases. In this part we will look a the results from our testing. Benchmark: tf_cnn_benchmarks suite (TensorFlow) The testing was done with tf_cnn_benchmarks, one of Tensorflow benchmark suites. This benchmark suite is designed for performance, since its models utilize the strategies employed in Read more...
In this two part series, we will look at leveraging NVIDIA GPU for Machine Learning in vSphere virtualized environments leveraging Bitfusion. In this first part, will discuss the options for sharing NVIDIA GPU, the setup of the infrastructure and the proposed test cases. In part two we will look at the results of the testing. Read more...
Want to learn more about virtualizing HPC and Deep Learning? VMware experts will be at PEARC18 (Practice and Experience in Advanced Research Computing) this week (July 22 -26, 2018) in Pittsburgh, PA. The theme of the conference this year is Seamless Creativity. VMware vSphere can help you increase your cluster efficiency, ensure security of the Read more...
Your company’s data scientists, machine learning practitioners or developers have asked you to provide them with a GPU-capable machine setup to do their work. They want to be able to execute workloads that need GPU compute power. The data scientist describes the workloads as machine learning “training”, “inference” or “development”. We will explain what they Read more...
Rightsizing a Machine Learning Cluster on VMware vSphere In part 1 of this 2-part article, we saw multiple applications running on Apache Spark clusters, the TensorFlow runtime, Cloudera CDH platform and other workloads – all sharing a set of physical servers that were managed by VMware vSphere. These applications operate in collections of virtual Read more...
