Accelerating the Cloud with GPUs

By Tiffany Trader

May 16, 2014

If you were to come up with a list of transformative technologies to hit HPC in the last decade, cloud services and general-purpose GPUs would rank pretty high. While the idea of using virtual machines to run technical computing workloads was anathema to some, at least initially, the benefits were hard to argue with. Ease of use, scalability, elasticity, and pay-as-you-go pricing were all major draws, but there was still the matter of overhead, i.e., the virtualization penalty. In terms of sheer performance, bare metal had the advantage.

As cloud grew in popularity, so did something called GPGPU computing, that is using general purpose graphics processing units to accelerate computing jobs. Perhaps the two technologies, GPUs and virtualization, could be combined to create a cloud environment that would satisfy the needs of HPC workloads. A group of computer scientists set out to explore this very question.

“We propose to bridge the gap between supercomputing and clouds by providing GPU-enabled virtual machines,” the team writes in a recently published paper. “Specifically, the Xen hypervisor is utilized to leverage specialized hardware-assisted I/O virtualization tools in order to provide advanced HPC-centric NVIDIA GPUs directly in guest VMs.”

It’s not the first time that GPU-enabled virtual machines have been tried. Amazon EC2 and a couple other cloud vendors have a GPU offering, however the approach is not without challenges and there are different ideas about how to best implement a GPU-based cloud environment, which the paper addresses.

The team of scientists, from Indiana University and the Information Sciences Institute (ISI), a unit of the University of Southern California’s Viterbi School of Engineering, compared the performance of two Tesla GPUs in a variety of applications using the native and the virtualized modes. To carry out the experiments, the researchers used two different machines, one outfitted with Fermi GPUs and and the other with newer Kepler chips. After running several benchmarks and assessing the results, the authors conclude that the GPU-backed virtual machines are viable for a range of scientific computing workflows. On average, the performance hit was 2.8 percent for Fermi GPUs and and 4.9 percent for Kepler GPUs.

In their comparison of virtualized environments with bare metal ones, the team studied three data points: FLOPS, device bandwidth and PCI bus performance. Among the more notable results in the FLOPS testing portion, the team found that even for double-precision FLOPS, the Kepler GPUs achieved nearly a doubling in performance. But more applicable to the research at hand, when it comes to raw FLOPS available to each GPU in both native and virtualized modes, the virtualization overhead was between 0 and 2.9 percent.

When other applications were tested, the performance penalty ranged from 0 percent in some cases to over 30 percent. The FFT benchmarks resulted in the most overhead, while the matrix multiplication based benchmarks had an average overhead of 2.9 percent for the virtualized setups.

In terms of device speed, which was measured in both raw bandwidth and 3rd party benchmarks, virtualization had “minimal or no significant performance impact.”

The final dimension being tested, the PCI express bus, had the highest potential for overhead, according to the research. “This is because the VT-d and IOMMU chip instruction sets interface directly with the PCI bus to provide operational and security related mechanisms for each PC device, thereby ensuring proper function in a multi-guest environment” the authors state. “As such, it is imperative to investigate any and all overhead at the PCI Express bus.”

In analyzing these results, the authors note that “as with all abstraction layers, some overhead is usually inevitable as a necessary trade-off to added feature sets and improved usability.”

While the same is true for GPU-equipped virtual machines, the research team contends that the overhead is minimal. They add that their method of direct PCI-Passthrough of NVIDIA GPUs using the Xeon hypervisor can be cleanly implemented within many Infrastructure-as-a-Service environments. The next step for the team will be integrating this model with the OpenStack nova IaaS framework with the aim of enabling researchers to create their own private clouds.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

‘Business Value’ of AI Heads Toward $4 Trillion

April 26, 2018

The rise of AI is reflected in recent market forecasts that predict it will help enterprises develop new products and services around applications like automated decision making. Market analyst Gartner Inc. forecasts Read more…

By George Leopold

Former AMD Chip Chief and ‘Zen’ Architect Jim Keller Joins Intel

April 26, 2018

Intel announced today it has hired top microprocessor architect Jim Keller as senior vice president to lead the company’s silicon engineering group, focusing on system-on-chip (SoC) development and integration. Read more…

By Tiffany Trader

Rackspace Is Latest to Roll Bare Metal Service

April 26, 2018

Rackspace is expanding its managed private cloud services with the addition of six new bare metal instances that it collectively refers to as bare metal as a service. The private cloud vendor announced the new managed Read more…

By George Leopold

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

Google Charts Two-Dimensional Quantum Course

April 26, 2018

Quantum error correction, essential for achieving universal fault-tolerant quantum computation, is one of the main challenges of the quantum computing field and it’s top of mind for Google’s John Martinis. At a presentation last week at the HPC User Forum in Tucson, Martinis, one of the world's foremost experts in quantum computing, emphasized... Read more…

By Tiffany Trader

Google Charts Two-Dimensional Quantum Course

April 26, 2018

Quantum error correction, essential for achieving universal fault-tolerant quantum computation, is one of the main challenges of the quantum computing field and it’s top of mind for Google’s John Martinis. At a presentation last week at the HPC User Forum in Tucson, Martinis, one of the world's foremost experts in quantum computing, emphasized... Read more…

By Tiffany Trader

Affordable Optical Technology Needed Says HPE’s Daley

April 26, 2018

While not new, the challenges presented by computer cabling/PCB circuit routing design – cost, performance, space requirements, and power management – have Read more…

By John Russell

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is Read more…

By Tiffany Trader

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Leading Solution Providers

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This