Will Public Clouds Ever Be Suitable for HPC?

By Nicole Hemsoth

June 27, 2010

For those who believe HPC is on the cusp of a revolution in terms of access and usability — especially for non-technical researchers — there are big, ever-lingering questions about how to make a general purpose cloud fit for HPC workloads. The end of most of these discussions comes when the topic of performance emerges because, let’s face it, there are not many appealing features to a large public cloud like Amazon for researchers with very specific compute demands. Having the power on demand is nice, but if the performance is the price to pay then it renders the idea useless.

If it’s a large public cloud we’re talking about — one that is most often used for scientific and large-scale enterprise computing — chances are it’s Amazon’s EC2. There are other public cloud providers, of course, but for the sake of argument, Amazon’s Elastic Compute offering is the poster child for cloud computing and often the first choice — if only because it has been around the longest. From startup cloud providers to big players, Amazon symbolizes the possibilities of cloud for everyone while it epitomizes the problems inherent to the cloud concept as it pertains to HPC.

Not to pick on EC2 here since there are several other public cloud providers to choose from, but it seems that most of the researchers who have made broader use of the public cloud, from large institutions down to individuals working on complex problems, have made this their premium choice. Will it stay this way forever? Probably not, especially since Microsoft and others are chomping at the bit for their share of the cloud movement with a direct focus on the HPC market. In fact, as it becomes clear that there might be benefits for scientific computing in the cloud at the same time that it is becoming glaringly obvious that the cloud-for-everyone will not apply for this specialized subset of users.

The Stagnant Public Cloud

It’s difficult to foster hope for greater use of the public cloud when it is not modified to any significant degree since its standard resources are providing enough to keep this end of the Amazon empire running.

Dr. Dieter Kranzlmuller in the German magazine Computer Woche suggested there are only very limited uses for the public cloud in HPC. “The effective use of a cloud is dependent on the applications. The cloud can be used appropriately when dealing with linear processes and independent, relatively small data volumes. For applications with larger storage requirements or closely coupled parallel processes with high I/O requirements, clouds are often useless.”

Way back in 2008, Edward Walker published a study entitled, “Benchmarking Amazon’s EC2 for High-Performance Scientific Computing” that provided results based on macro and micro comparison points to form a solid theory about the performance gap in the public cloud, even with equivalent processing power. This of course boils down to the MPI and interconnects issue — just as it still does today. The mere act of virtualization renders the cloud almost useless to many scientific HPC clusters, in other words.

According to Walker in his older yet still just-as-relevant report based on the benchmarking study, “the delivery of HPC performance with commercial cloud computing services such as Amazon EC2 is not yet mature…a performance gap exists between performing HPC computations on a traditional scientific cluster and on an EC2 provisioned scientific cluster. This performance gap is seen not only in the MPI performance of distributed-memory parallel programs but also in the single compute node OpenMP performance for shared-memory parallel programs. For cloud computing to be a viable alternative for the computational science community, vendors will need to upgrade their service offerings, especially in the area of high-performance network provisioning to cater to this unique class of users.”

Since the vendor in question here — Amazon — has not upgraded its service offerings, the time has come for others to pick up the slack and create specialized cloud environments that are in tune with the performance demands of HPC users if the cloud vision is to be realized for its cost benefits.

None of this portends well for strict HPC applications in a large public cloud offering like Amazon’s. EC2 and other public clouds designed to run everything from big commercial websites to outsourced large batch jobs might seem appealing on a cursory glance to many, but as William Fellows, analyst at the 451 Group, stated, “The main problem with running HPC tasks on conventional clouds is that conventional clouds are geared toward supporting general-purposes applications and services — short transactional workloads such as web applications and database tasks…theses are heavily dependent on the need to be processed serially and within an infrastructure geared toward supporting inter-process communication.”

In other words, the public cloud is designed for an admirably long list of workloads but HPC in general — not so much. But really, when you get right down to it, why should EC2 change its style to fit the needs of scientific users in the first place when it is doing just fine serving the needs of mainstream users? After all, other companies who already have some degree of HPC supremacy are making headway as they are better positioned to tailor their approach to coaxing researchers on to their clouds — in whatever form they’ve devised.

Bridges Across the Performance Chasm

When so many think about the cloud in general, the first thought is about large-scale cloud providers like Amazon, but the fact is, there are an increasing number of choices that remove the performance gap caused by virtualization or that have clouds that are tailored to the performance-driven needs of HPC users.

IBM, Microsoft, SGI, Penguin, Cycle and a handful of others that do not work directly to manage their clients’ push to the public cloud via a layer of cloud management software are doing so in part because they’ve realized that there is no broad appeal for true, traditional HPC users to move to EC2. They realize that the environment needs to be customized, that the performance is the most critical factor in gaining converts — and most importantly, that there is no public cloud that can beat the power of a cluster. So in a manner that screams “grid” they are renting specialized clusters that are specifically designed for HPC users.

In an effort to overcome the performance gap yet still provide users with the freedom of owning and managing their own clusters, Penguin On-Demand (POD) and others, including Cycle Computing, are taking the concept of the cloud for HPC and making it more attractive to HPC users by eliminating the virtualization and providing customized servers. This missing layer of virtualization adds some complication to the term “cloud” but it is a logical step for researchers who are attracted to the cost benefits of avoiding the expense of a cluster investment. Since many HPC users have found that large public clouds, most notably Amazon’s EC2, do not offer the service levels they depend on, it is reasonable to predict that there will be a host of new upstarts that seek to bring dedicated servers to researchers in an on-demand fashion versus creating a complex management layer that is tied to the public cloud.

This is not to say that EC2 is not being used with some success, but most often these are jobs are that are not necessarily HPC-like. As Kathy Yelick, director of NERSC, noted in a recent interview about current developments in the Magellan cloud, “there’s a part of the workload in scientific computing that’s well-suited to the cloud, but it’s not the HPC end, it’s really the bulk aggregate serial workload that often comes up in scientific computing, but that is not really the traditional arena of high-performance computing.”

If existing cloud providers with their eyes on the HPC market can better tailor their solutions to meet the broader range of HPC application needs with a distinct focus on performance, it stands to reason that the world of the public cloud will be out of reach to Amazon and other general purpose cloud providers.

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!

US Exascale Computing Update with Paul Messina

December 8, 2016

Around the world, efforts are ramping up to cross the next major computing threshold with machines that are 50-100x more performant than today’s fastest number crunchers.  Read more…

By Tiffany Trader

Weekly Twitter Roundup (Dec. 8, 2016)

December 8, 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

Qualcomm Targets Intel Datacenter Dominance with 10nm ARM-based Server Chip

December 8, 2016

Claiming no less than a reshaping of the future of Intel-dominated datacenter computing, Qualcomm Technologies, the market leader in smartphone chips, announced the forthcoming availability of what it says is the world’s first 10nm processor for servers, based on ARM Holding’s chip designs. Read more…

By Doug Black

Which Schools Produce the Top Coders in the World?

December 8, 2016

Ever wonder which universities worldwide produce the best coders? The answers may surprise you, at least as judged by the results of a competition posted yesterday on the HackerRank blog. Read more…

By John Russell

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. The pilots, supported in part by DOE exascale funding, not only seek to do good by advancing cancer research and therapy but also to advance deep learning capabilities and infrastructure with an eye towards eventual use on exascale machines. Read more…

By John Russell

DDN Enables 50TB/Day Trans-Pacific Data Transfer for Yahoo Japan

December 6, 2016

Transferring data from one data center to another in search of lower regional energy costs isn’t a new concept, but Yahoo Japan is putting the idea into transcontinental effect with a system that transfers 50TB of data a day from Japan to the U.S., where electricity costs a quarter of the rates in Japan. Read more…

By Doug Black

Infographic Highlights Career of Admiral Grace Murray Hopper

December 5, 2016

Dr. Grace Murray Hopper (December 9, 1906 – January 1, 1992) was an early pioneer of computer science and one of the most famous women achievers in a field dominated by men. Read more…

By Staff

Ganthier, Turkel on the Dell EMC Road Ahead

December 5, 2016

Who is Dell EMC and why should you care? Glad you asked is Jim Ganthier’s quick response. Ganthier is SVP for validated solutions and high performance computing for the new (even bigger) technology giant Dell EMC following Dell’s acquisition of EMC in September. In this case, says Ganthier, the blending of the two companies is a 1+1 = 5 proposition. Not bad math if you can pull it off. Read more…

By John Russell

US Exascale Computing Update with Paul Messina

December 8, 2016

Around the world, efforts are ramping up to cross the next major computing threshold with machines that are 50-100x more performant than today’s fastest number crunchers.  Read more…

By Tiffany Trader

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. The pilots, supported in part by DOE exascale funding, not only seek to do good by advancing cancer research and therapy but also to advance deep learning capabilities and infrastructure with an eye towards eventual use on exascale machines. Read more…

By John Russell

Ganthier, Turkel on the Dell EMC Road Ahead

December 5, 2016

Who is Dell EMC and why should you care? Glad you asked is Jim Ganthier’s quick response. Ganthier is SVP for validated solutions and high performance computing for the new (even bigger) technology giant Dell EMC following Dell’s acquisition of EMC in September. In this case, says Ganthier, the blending of the two companies is a 1+1 = 5 proposition. Not bad math if you can pull it off. 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

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

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

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

Leading Solution Providers

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

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

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