• Skip to main content
  • Skip to secondary menu
  • Skip to footer

Technologies.org

Technology Trends: Follow the Money

  • Technology Events 2026-2027
  • Sponsored Post
  • Technology Markets
  • About
    • GDPR
  • Contact

Mellanox Works With VMware and NVIDIA to Enable High Performance Virtualized Machine Learning Solutions

August 27, 2019 By admin Leave a Comment

VMworld 2019 – Mellanox Technologies, Ltd. (NASDAQ: MLNX), a leading supplier of high-performance, end-to-end smart interconnect solutions for data center servers and storage systems, today 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. Benchmarks demonstrate that the NVIDIA® vComputeServer (vCS) for virtualized GPUs achieve two times better efficiency by using VMware’s paravirtualized RDMA (PVRDMA) technology than when using traditional networking protocols. The benchmark was performed on a four-node cluster running vSphere 6.7 equipped with NVIDIA T4 GPUs with vCS software and Mellanox ConnectX-5 100 GbE SmartNICs, all connected by a Mellanox Spectrum SN2700 100 GbE switch.

The PVRDMA Ethernet solution enables VM-to-VM communication over RDMA, which boosts data communication performance in virtualized environments while achieving significantly higher efficiency compared with legacy TCP/IP transports. Additionally, PVRDMA retains core virtual machine capabilities such as vMotion. This translates to real-world customer advantages including optimized server and GPU utilization, reduced machine learning training time and improved scalability. Using PVRDMA also shrinks backup times, improves data center simplicity, simplifies consolidation, lowers power consumption and reduces total cost of ownership.

“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, senior 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.”

NVIDIA T4 GPUs supercharge the world’s most trusted mainstream servers, easily fitting into standard data center infrastructures. Their low-profile, 70-watt design is powered by NVIDIA Turing™ Tensor Cores, delivering revolutionary multi-precision performance to accelerate a wide range of modern applications, including machine learning, deep learning, and virtual desktops. With the latest vComputeServer software for GPU virtualization, it also provides maximum performance and manageability for AI, ML and data science workloads in a virtualized server environment.

“Machine learning has become extremely important and every company, regardless of size, must leverage its power to remain competitive,” said Bob Pette, vice president, Professional Visualization NVIDIA. “Our collaboration with VMware and Mellanox creates a high-performance GPU platform that enables acceleration for compute-intensive workloads in the most efficient way.”

Machine learning workloads are extremely resource intensive, often relying on hardware acceleration to achieve the performance necessary to solve large, complex problems in a timely manner. Interconnect acceleration – special hardware that delivers extremely high bandwidth and low latency, and compute acceleration – often delivered through exploitation of very highly-parallel GPU compute engines, are the most common forms of such acceleration. While both types of acceleration have long been available on vSphere, it is now possible with vSphere to combine these technologies to support advanced machine learning applications that allow applications to combine the compute power of NVIDIA GPUs with the high-performance data transfer capabilities of Mellanox RDMA capable adapters, enabling linear scalability.

“Modern data center infrastructures need to keep pace with the compute and efficiency requirements for the exceedingly complex machine learning computational models,” said Sudhanshu (Suds) Jain, Product Management, Cloud Platform Business Units, VMware. “The ability to virtualize GPUs using the latest NVIDIA vComputeServer product and Mellanox’s high-speed networking solutions over vSphere makes it possible to meet those requirements while keeping the cost intact.”

Availability
VMware vSphere is fully qualified with Mellanox ConnectX 10/25/40/50/100G adapters today. All Mellanox adapters support PVRDMA over RoCE (RDMA over Converged Ethernet), enabling advanced capabilities like GPU virtualization, and making data center infrastructure RoCE-Ready as new technologies over RDMA become generally available. PVRDMA will also be supported by the latest ConnectX-6 Dx and BlueField-2 SmartNICs announced today at VMworld.

About Mellanox
Mellanox Technologies (NASDAQ: MLNX) is a leading supplier of end-to-end Ethernet and InfiniBand smart interconnect solutions and services for servers and storage. Mellanox interconnect solutions increase data center efficiency by providing the highest throughput and lowest latency, delivering data faster to applications, unlocking system performance and improving data security. Mellanox offers a choice of fast interconnect products: adapters, switches, software and silicon that accelerate application performance and maximize business results for a wide range of markets including cloud and hyperscale, high performance computing, artificial intelligence, enterprise data centers, cyber security, storage, financial services and more. More information is available at: www.mellanox.com.

Filed Under: Tech Tagged With: AI, GPU, ML, Machine Learning, Mellanox, NVIDIA, VMware, deep learning, high performance computing, virtual desktop, virtualized server environment

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Footer

Recent Posts

  • Apple Unveils MacBook Neo: A $599 Entry Into the Mac Ecosystem
  • Apple Unveils M5 Pro and M5 Max: A New Era for MacBook Pro, MacBook Air, and Studio Display
  • Apple iPhone 17e: Performance, Practicality, and a Smarter Entry Point into the iPhone 17 Family
  • Apple iPad Air M4 Arrives With 12GB Memory, Wi-Fi 7, and a Serious AI Push
  • Ericsson and Intel Are Redefining What 6G Is Actually For
  • Hollow-Core Fibre, Light Running Through Air Instead of Glass
  • Revel Raises $150M to Modernize the Software Backbone of Mission-Critical Hardware
  • Samsung Galaxy S26 Series: Polished, Predictable, and Playing It Safe
  • SambaNova Unveils SN50 AI Chip, Secures $350M+ Funding, and Strikes Strategic Intel Partnership
  • Aalyria Raises $100M Series B to Build the Control Plane for the Space Internet

Media Partners

  • Market Analysis
  • Cybersecurity Market
Memory Crunch: Why Prices Are Surging and Why Making More Memory Isn’t Easy
The End of Accounting as We Knew It
The Era of Superhuman Logistics Has Arrived: Building the First Autonomous Freight Network
Why Nvidia Shares Jumped on Meta, and Why the Market Cared
Accrual Launches With $75M to Push AI-Native Automation Into Core Accounting Workflows
Europe’s Digital Sovereignty Moment, or How Regulation Became a Competitive Handicap
Palantir Q4 2025: From Earnings Beat to Model Re-Rating
Baseten Raises $300M to Dominate the Inference Layer of AI, Valued at $5B
Nvidia’s China Problem Is Self-Inflicted, and Washington Should Stop Pretending Otherwise
USPS and the Theater of Control: How Government Freezes Failure in Place
Day Zero Threat Research Summit, August 30 – September 1, 2026, Las Vegas
CrowdStrike Returns to Profit as Revenue Climbs to $1.31 Billion in Q4
Cloudflare 2026 Threat Report Signals the Automation of Cyberwar
Fal.Con Gov 2026, March 18, Washington, D.C.
Huper Corporation Raises $1.5M Pre-Seed to Build a Security-First AI Chief of Staff
CyberBay Summit 2026, March 11–13, Tampa, Florida
Zscaler’s Q2 Beat and the Market’s Reluctance to Celebrate
AI as the New Insider: Why Trust, Not Code, Is Now the Weakest Link
Cybersecurity Meets Corporate Travel: Darktrace Chooses AI-Driven Navan to Power Global Mobility
Black Hat Asia 2026, April 21–24, Singapore

Media Partners

  • Market Research Media
  • Technology Conferences
The Rise of Faceless Creators: Picsart Launches Persona and Storyline for AI Character-Driven Content
Apple TV Arrives on The Roku Channel, Expanding the Streaming Platform Wars
Why Attraction-Grabbing Stations Win at Tech Events
Why Nvidia Let Go of Arm, and Why It Matters Now
When the Market Wants a Story, Not Numbers: Rethinking AMD’s Q4 Selloff
BBC and the Gaza War: How Disproportionate Attention Reshapes Reality
Parallel Museums: Why the Future of Art Might Be Copies, Not Originals
ClickHouse Series D, The $400M Bet That Data Infrastructure, Not Models, Will Decide the AI Era
AI Productivity Paradox: When Speed Eats Its Own Gain
Voice AI as Infrastructure: How Deepgram Signals a New Media Market Segment
COMPUTEX 2026, June 2–5, Taipei
360° Mobility Mega Shows 2026, April 14–17, Taipei
Forrester CX Summit Series 2026: Amsterdam, New York, San Francisco
IAMPHENOM 2026, March 10–12, Pennsylvania Convention Center, Philadelphia
Billington State and Local CyberSecurity Summit, March 9–11, 2026, Washington, D.C.
Mobile World Congress (MWC) 2026 – 2–5 March, Barcelona, Spain
The AI Summit London, 10–11 June 2026, Tobacco Dock, London
aim10x Digital 2026, March 18, Virtual
Harvard Business Review Strategy Summit, February 26, 2026, Virtual
International Compact Modeling Conference, July 30–31, 2026, Long Beach, California

Copyright © 2022 Technologies.org

Media Partners: Market Analysis & Market Research and Exclusive Domains, Photography