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!

UK to Launch Six Major HPC Centers

March 27, 2017

Six high performance computing centers will be formally launched in the U.K. later this week intended to provide wider access to HPC resources to U.K. Read more…

By John Russell

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Quants Achieving Maximum Compute Power without the Learning Curve

The financial services industry is a fast-paced and data-intensive environment, and financial firms are realizing that they must modernize their IT infrastructures and invest in high performance computing (HPC) tools in order to survive. Read more…

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

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

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Leading Solution Providers

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. 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

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

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