Palm Trees, HPC and Virtualization

By Wolfgang Gentzsch

May 21, 2010

We were lounging in the paradise-like ambience of the beautiful conference hotel in Hammamet, Tunisia, earlier this week, under a verdant canopy of palm trees near the beach — not a cloud to be seen. The AICCSA International Conference on Computer Systems and Applications was in full swing, where Dr. Mazin Yousif just presented the keynote on cloud computing.

Shortly after Mazin joined Intel in 2000 to work on InfiniBand, I remember, we worked together on self-adaptable grid architecture. He then got into HPC when he was the chair of the Management Working Group (MgtWG) of the InfiniBand Trade Association (IBTA) which defined the management architecture for the InfiniBand Architecture (IBA). For many of the TOP500 HPC systems today, InfiniBand is the underlying interconnect technology, optimized for high-bandwidth low-latency communication.

Through InfiniBand, HPC applications, after establishing the interconnect channel, have direct access to the hardware, bypassing the operating system and the device drivers, reducing latency to a few hundred nanoseconds. (Ethernet, on the other hand, where communication moves through the TCP transport layer, IP network layer, link layer and physical layer, is an order of magnitude slower). I found that Mazin, equipped with this expertise, was the ideal person to answer my question about how virtualization in cloud computing really affects the performance of our HPC applications. The following is the result of our conversation HPC and virtualization — under the palms.

Wolfgang Gentzsch: We hear a lot about the additional overhead caused by virtualization, these days. How does virtualization really affect the performance of HPC applications?

Mazin Yousif: To answer this question, we first should look at the role of the VMM (the virtual machine monitor, also called hypervisor). The VMM sits directly on top of the hardware, abstracting all the hardware resources into virtual resources that get aggregated and launched as Virtual Machines (VMs, the containers that run the whole software stack). Usually, the VMM also hosts the device drivers for accessing I/O resources, causing extra overhead for I/O requests.

Gentzsch: Does this mean that the performance of mainly compute-intensive applications wouldn’t be affected by the virtualization?

Yousif: Yes, if compute-intensive applications run completely within the VM with very limited enters to and exits from the VMM, the impact on the overall performance is very minimal.

Gentzsch: … and I/O-intensive applications?

Yousif: There, the overhead is going to be noticeable because all I/O requests inside the VM cause jumps to the VMM, where the I/O device drivers are accessed, and enabling access to the physical I/O resource. This usually causes an extra overhead of a few microseconds. In a more realistic HPC scenario with a mix of compute- and I/O-intensive operations, the amount of overhead is certainly somewhere in-between.

Gentzsch: Could I avoid this overhead at all?

Yousif: May be not completely, but in principle, yes. First, VM vendors could further optimize the VMM, for example by reducing the critical path for an I/O operation within the VMM code. Second, instead of going through the VMM, an I/O device could be directly assigned to a VM which would eliminate the overhead caused by the VMM. This can be achieved by configuring the VMM, resulting in a much better I/O performance. The disadvantage however is that now you need an I/O device for every VM, instead of sharing that device among several VMs, as is usual.

Gentzsch: … but isn’t it better to optimize the rate of completing HPC transactions, rather than focusing on latency alone?

Yousif: Indeed. I see rate as more important than latency alone since rate involves both bandwidth and latency (=BW/latency). Virtualization not only impacts latency, but also impacts bandwidth as well. As before, in a mainly compute-intensive workload that fits in the allocated VM memory, rate will not see any depreciation compared to running the same workload on physical resources. In a mixed-traffic workload, relying on an assigned I/O device helps considerably here.

Gentzsch: When you assign a number of VMs to run an HPC workload, would it be better to keep the environment as is for the duration of the run or should it be adapted to track workload resources’ requirements changes?

Yousif: I see it as necessary to adapt the number and configuration of VMs based on the workload’s resources requirements, as well as the service-level agreements the owner of the workload signed with the cloud provider. To track workload changes, the VMM includes provisions to scale resources assigned to a VM up or down based on that VM’s resource needs. If the elasticity provided by the VMM is not sufficient, then other capabilities such as VMware’s Distributed Resource Scheduling along with VMotion can do the trick.

Gentzsch: So what would I have to do, as an HPC user?

Yousif: If you have a feel about the mix of compute versus I/O intensity in your HPC application, you can decide whether to assign an I/O device directly to a VM or not. If, for example, your working set fits completely into the main memory allocated to a VM, there is obviously no I/O, no page faults, no disc swaps, and thus no overhead.

Gentzsch: But that means that I have to have the ability to configure my VMM. I understand that this can be done in my private cloud, but how would I do this in IBM’s public cloud, for example?

Yousif: Today you can’t. Public cloud service providers currently do not allow HPC end-users to decide whether to assign an I/O device per VM or to share it among several VMs. If there is a real need for this, the HPC community should request this feature from the public cloud service providers to enable HPC in the public clouds.

Gentzsch: So what would be your conclusion and recommendation?

Yousif: I do not see major obstacles running HPC workloads in virtualized environments as there are ways to mitigate the overhead incurred through the VMM. But to cater further to the HPC community, we urge the cloud providers to incorporate running IBA in a virtualized environment in their cloud deployments, which could be one of the best choices for the HPC community as, first, IBA is much easier to virtualize than other I/O technologies, and second, at the same time it offers much better performance than other I/O technologies. Cloud providers currently do not offer IBA support in their cloud deployments.

Addendum on Virtualization

When I checked the dictionary to learn the meaning of virtual, here is what I found, “Vir•tu•al (adjective): existing in essence or effect, though not in actual fact.” Now, virtual systems are systems that: (i) incorporate hardware-level abstraction of physical resources including processors, memory, chipset, I/O devices and others ; and (ii) encapsulate all OS & application state. This is done through the VMM virtualization software that: (i) provides extra level of indirection and decouples hardware & OS; (ii) multiplexes physical hardware across multiple Guest VMs; (iii) provides better strong isolation between VMs; and (iv) manages physical resources and improves utilization.

Virtualization provides a great deal of benefits including, but not limited to, (i) considerably increasing utilization from <15 percent to much higher numbers that can reach 90 percent; (ii) through isolation, it allows to run multiple VMs on a single physical host, and any software malware or crashes in one VM do not affect other VMs; (iii) through encapsulation, it is possible to have the entire VM (including OS, applications, data, memory and device state) as a file that will allow us to, for example, take snapshots, clones, backup, capture a VM state on the fly and restore to point-in-time; (iv) reduce total cost of ownership; and many more.

In terms of uses, examples include test and development; server consolidation and containment; and enterprise virtual desktops.

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!

AWS Embraces FPGAs, ‘Elastic’ GPUs

December 2, 2016

A new instance type rolled out this week by Amazon Web Services is based on customizable field programmable gate arrays that promise to strike a balance between performance and cost as emerging workloads create requirements often unmet by general-purpose processors. Read more…

By George Leopold

AWS Launches Massive 100 Petabyte ‘Sneakernet’

December 1, 2016

Amazon Web Services now offers a way to move data into its cloud by the truckload. Read more…

By Tiffany Trader

Weekly Twitter Roundup (Dec. 1, 2016)

December 1, 2016

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

HPC Career Notes (Dec. 2016)

December 1, 2016

In this monthly feature, we’ll keep you up-to-date on the latest career developments for individuals in the high performance computing community. Read more…

By Thomas Ayres

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

IBM and NSF Computing Pioneer Erich Bloch Dies at 91

November 30, 2016

Erich Bloch, a computational pioneer whose competitive zeal and commercial bent helped transform the National Science Foundation while he was its director, died last Friday at age 91. Bloch was a productive force to be reckoned. During his long stint at IBM prior to joining NSF Bloch spearheaded development of the “Stretch” supercomputer and IBM’s phenomenally successful System/360. Read more…

By John Russell

Pioneering Programmers Awarded Presidential Medal of Freedom

November 30, 2016

In an awards ceremony on November 22, President Barack Obama recognized 21 recipients with the Presidential Medal of Freedom, the Nation’s highest civilian honor. Read more…

By Tiffany Trader

Seagate-led SAGE Project Delivers Update on Exascale Goals

November 29, 2016

Roughly a year and a half after its launch, the SAGE exascale storage project led by Seagate has delivered a substantive interim report – Data Storage for Extreme Scale. Read more…

By John Russell

AWS Launches Massive 100 Petabyte ‘Sneakernet’

December 1, 2016

Amazon Web Services now offers a way to move data into its cloud by the truckload. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Seagate-led SAGE Project Delivers Update on Exascale Goals

November 29, 2016

Roughly a year and a half after its launch, the SAGE exascale storage project led by Seagate has delivered a substantive interim report – Data Storage for Extreme Scale. Read more…

By John Russell

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

HPE-SGI to Tackle Exascale and Enterprise Targets

November 22, 2016

At first blush, and maybe second blush too, Hewlett Packard Enterprise’s (HPE) purchase of SGI seems like an unambiguous win-win. SGI’s advanced shared memory technology, its popular UV product line (Hanna), deep vertical market expertise, and services-led go-to-market capability all give HPE a leg up in its drive to remake itself. Bear in mind HPE came into existence just a year ago with the split of Hewlett-Packard. The computer landscape, including HPC, is shifting with still unclear consequences. One wonders who’s next on the deal block following Dell’s recent merger with EMC. Read more…

By John Russell

Intel Details AI Hardware Strategy for Post-GPU Age

November 21, 2016

Last week at SC16, Intel revealed its product roadmap for embedding its processors with key capabilities and attributes needed to take artificial intelligence (AI) to the next level. Read more…

By Alex Woodie

SC Says Farewell to Salt Lake City, See You in Denver

November 18, 2016

After an intense four-day flurry of activity (and a cold snap that brought some actual snow flurries), the SC16 show floor closed yesterday (Thursday) and the always-extensive technical program wound down today. Read more…

By Tiffany Trader

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

Why 2016 Is the Most Important Year in HPC in Over Two Decades

August 23, 2016

In 1994, two NASA employees connected 16 commodity workstations together using a standard Ethernet LAN and installed open-source message passing software that allowed their number-crunching scientific application to run on the whole “cluster” of machines as if it were a single entity. Read more…

By Vincent Natoli, Stone Ridge Technology

IBM Advances Against x86 with Power9

August 30, 2016

After offering OpenPower Summit attendees a limited preview in April, IBM is unveiling further details of its next-gen CPU, Power9, which the tech mainstay is counting on to regain market share ceded to rival Intel. Read more…

By Tiffany Trader

AWS Beats Azure to K80 General Availability

September 30, 2016

Amazon Web Services has seeded its cloud with Nvidia Tesla K80 GPUs to meet the growing demand for accelerated computing across an increasingly-diverse range of workloads. The P2 instance family is a welcome addition for compute- and data-focused users who were growing frustrated with the performance limitations of Amazon's G2 instances, which are backed by three-year-old Nvidia GRID K520 graphics cards. Read more…

By Tiffany Trader

Think Fast – Is Neuromorphic Computing Set to Leap Forward?

August 15, 2016

Steadily advancing neuromorphic computing technology has created high expectations for this fundamentally different approach to computing. Read more…

By John Russell

The Exascale Computing Project Awards $39.8M to 22 Projects

September 7, 2016

The Department of Energy’s Exascale Computing Project (ECP) hit an important milestone today with the announcement of its first round of funding, moving the nation closer to its goal of reaching capable exascale computing by 2023. Read more…

By Tiffany Trader

HPE Gobbles SGI for Larger Slice of $11B HPC Pie

August 11, 2016

Hewlett Packard Enterprise (HPE) announced today that it will acquire rival HPC server maker SGI for $7.75 per share, or about $275 million, inclusive of cash and debt. The deal ends the seven-year reprieve that kept the SGI banner flying after Rackable Systems purchased the bankrupt Silicon Graphics Inc. for $25 million in 2009 and assumed the SGI brand. Bringing SGI into its fold bolsters HPE's high-performance computing and data analytics capabilities and expands its position... Read more…

By Tiffany Trader

ARM Unveils Scalable Vector Extension for HPC at Hot Chips

August 22, 2016

ARM and Fujitsu today announced a scalable vector extension (SVE) to the ARMv8-A architecture intended to enhance ARM capabilities in HPC workloads. Fujitsu is the lead silicon partner in the effort (so far) and will use ARM with SVE technology in its post K computer, Japan’s next flagship supercomputer planned for the 2020 timeframe. This is an important incremental step for ARM, which seeks to push more aggressively into mainstream and HPC server markets. Read more…

By John Russell

IBM Debuts Power8 Chip with NVLink and Three New Systems

September 8, 2016

Not long after revealing more details about its next-gen Power9 chip due in 2017, IBM today rolled out three new Power8-based Linux servers and a new version of its Power8 chip featuring Nvidia’s NVLink interconnect. Read more…

By John Russell

Leading Solution Providers

Vectors: How the Old Became New Again in Supercomputing

September 26, 2016

Vector instructions, once a powerful performance innovation of supercomputing in the 1970s and 1980s became an obsolete technology in the 1990s. But like the mythical phoenix bird, vector instructions have arisen from the ashes. Here is the history of a technology that went from new to old then back to new. Read more…

By Lynd Stringer

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Intel Launches Silicon Photonics Chip, Previews Next-Gen Phi for AI

August 18, 2016

At the Intel Developer Forum, held in San Francisco this week, Intel Senior Vice President and General Manager Diane Bryant announced the launch of Intel's Silicon Photonics product line and teased a brand-new Phi product, codenamed "Knights Mill," aimed at machine learning workloads. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Beyond von Neumann, Neuromorphic Computing Steadily Advances

March 21, 2016

Neuromorphic computing – brain inspired computing – has long been a tantalizing goal. The human brain does with around 20 watts what supercomputers do with megawatts. And power consumption isn’t the only difference. Fundamentally, brains ‘think differently’ than the von Neumann architecture-based computers. While neuromorphic computing progress has been intriguing, it has still not proven very practical. Read more…

By John Russell

Dell EMC Engineers Strategy to Democratize HPC

September 29, 2016

The freshly minted Dell EMC division of Dell Technologies is on a mission to take HPC mainstream with a strategy that hinges on engineered solutions, beginning with a focus on three industry verticals: manufacturing, research and life sciences. "Unlike traditional HPC where everybody bought parts, assembled parts and ran the workloads and did iterative engineering, we want folks to focus on time to innovation and let us worry about the infrastructure," said Jim Ganthier, senior vice president, validated solutions organization at Dell EMC Converged Platforms Solution Division. Read more…

By Tiffany Trader

Container App ‘Singularity’ Eases Scientific Computing

October 20, 2016

HPC container platform Singularity is just six months out from its 1.0 release but already is making inroads across the HPC research landscape. It's in use at Lawrence Berkeley National Laboratory (LBNL), where Singularity founder Gregory Kurtzer has worked in the High Performance Computing Services (HPCS) group for 16 years. Read more…

By Tiffany Trader

Micron, Intel Prepare to Launch 3D XPoint Memory

August 16, 2016

Micron Technology used last week’s Flash Memory Summit to roll out its new line of 3D XPoint memory technology jointly developed with Intel while demonstrating the technology in solid-state drives. Micron claimed its Quantx line delivers PCI Express (PCIe) SSD performance with read latencies at less than 10 microseconds and writes at less than 20 microseconds. Read more…

By George Leopold

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