SANTA CLARA, Calif., Aug. 30, 2022 — AMD (NASDAQ: AMD) announced that the AMD Pensando Distributed Services Card will be one of the first data processing unit solutions to support VMware vSphere 8 available from server vendors including Dell Technologies, HPE and Lenovo. As data center applications grow in scale and sophistication, the resulting workloads […]
Nvidia Announces GA of AI Enterprise on VMware vSphere and Standard Servers
NVIDIA today announced GA of NVIDIA AI Enterprise, a suite of AI tools and frameworks designed to enable users of VMware vSphere to virtualize AI workloads on NVIDIA-Certified Systems. Systems makers Atos, Dell Technologies, GIGABYTE, Hewlett Packard Enterprise, Inspur, Lenovo and Supermicro are offering NVIDIA-Certified Systems optimized for AI workloads on VMware vSphere with NVIDIA […]
Bright Computing Cluster as a Service for VMware
This whitepaper from Bright Computing discusses how through advanced automation, Bright Cluster Manager eliminates the complexity of building and managing high-performance Linux clusters, enabling greater organizational efficiency and flexibility. And now, Bright Cluster Manager also supports clusters in VMware vSphere—and goes one step further to enable high-performance clusters as a service.
Nvidia Unveils AI Enterprise Software Suite with VMware vSphere 7
SANTA CLARA, Calif., March 09, 2021 – Nvidia today announced AI Enterprise, a software suite of enterprise-grade AI development tools and frameworks supported by Nvidia with VMware vSphere 7 Update 2. Nvidia said the software suite enables vSphere compute virtualization users to build AI applications with the same tools they use to manage data centers […]
Mellanox Powers Virtualized Machine Learning with VMware and NVIDIA
Today Mellanox announced that its RDMA (Remote Direct Memory Access) networking solutions for VMware vSphere enable virtualized Machine Learning solutions that achieve higher GPU utilization and efficiency. “As Moore’s Law has slowed, traditional CPU and networking technologies are no longer sufficient to support the emerging machine learning workloads,” said Kevin Deierling, vice president marketing, Mellanox Technologies. “Using hardware compute accelerators such as NVIDIA T4 GPUs and Mellanox’s RDMA networking solutions has proven to boost application performance in virtualized deployments.”
Accelerating Machine Learning on VMware vSphere with NVIDIA GPUs
Mohan Potheri from VMware gave this talk at Stanford HPC Conference. “This session introduces machine learning on vSphere to the attendee and explains when and why GPUs are important for them. Basic machine learning with Apache Spark is demonstrated. GPUs can be effectively shared in vSphere environments and the various methods of sharing are addressed here.”
VMware Powers Machine Learning & HPC Workloads
In this video from SC18 in Dallas, Ziv Kalminovich from VMware describes how the company’s powerful virtualization capabilities bring flexibility and performance to HPC workloads. “With VMware, you can capture the benefits of virtualization for HPC workloads while delivering performance that is comparable to bare-metal. Our approach to virtualizing HPC adds a level of flexibility, operational efficiency, agility and security that cannot be achieved in bare-metal environments—enabling faster time to insights and discovery.”
Virtualization Adds Value, Benefits to HPC Environments
VMware explores the concepts of virtual throughput clusters and CPU overcommitment with VMware vSphere to create multitenant and agile virtual HPC computing environments.
Virtualizing AI & HPC Workloads with vSphere
In this video from the Dell EMC HPC Community Meeting, Josh Simons from VMware describes why more customers are moving their HPC & AI workloads to virtualized environments using vSphere. “With VMware, you can capture the benefits of virtualization for HPC workloads while delivering performance that is comparable to bare-metal. Our approach to virtualizing HPC adds a level of flexibility, operational efficiency, agility and security that cannot be achieved in bare-metal environments—enabling faster time to insights and discovery.”