Cloud Computing Opportunities in HPC

By Christopher G. Willard, Ph.D., Addison Snell, Laura Segervall

November 2, 2009

This article is excerpted from “Cloud Opportunities in HPC: Market Taxonomy,” published by InterSect360 Research. The full article was distributed to subscribers of the InterSect360 market advisory service and can also be obtained by contacting sales@intersect360.com.

In Life, the Universe, and Everything, the third book of Douglas Adams’ whimsical Hitchhiker fantasy trilogy, cosmic wayfarer Ford Prefect describes how an object, even a large object, could effectively be rendered invisible to the general populace by surrounding it with an “SEP field” that causes would-be observers to avoid recognizing Somebody Else’s Problem. “An SEP,” Ford helpfully explains, “is something we can’t see, or don’t see, or our brain doesn’t let us see, because we think that it’s somebody else’s problem.”

If we were to reinterpret SEP to stand for “Somebody Else’s Processing,” we would be well on the way to a definition of cloud computing.

The term “cloud” comes from the engineering practice of drawing a cloud in a schematic to represent an external resource that the engineer’s design will interact with — a part of the workflow that he or she will assume is working but that is not part of that specific design. For example, a processor designer might draw a cloud to represent a memory system, with arrows indicating the flow of data in and out of the memory cloud. Cloud computing takes this concept to an organizational level; entire sections of IT workflows can now be virtualized into resources that are someone else’s concern.

Cloud computing is therefore a new instantiation of distributed computing. It is built on grid computing concepts and technology and further enabled by Internet technologies for access. Cloud computing is the delivery of some part of an IT workflow — such as computational cycles, data storage, or application hosting — using an Internet-style interface. This definition includes Web-immersed intranets as conduits for accessing private clouds.

Cloud computing is currently driven by business models that attempt to utilize or monetize unused resources. Grid, virtualization, and now cloud technologies have attempted to find and tap idle resources, thus reducing costs or generating revenue. The most interesting difference between cloud computing and earlier forms of distributed computing is that in developing ultra-scale computing centers, organizations such as Google and Amazon incidentally built out significant caches of occasionally idle computing resources that could be made generally available through the Internet. Furthermore these organizations found that they had developed significant skills in constructing and managing these resources, and economies of scale allowed them to purchase incremental equipment at relatively lower prices. The cloud was born as an effort to monetize those skills, economic advantages, and excess capacity.

This is important because from a business model point of view the cloud resources came into existence at no cost, with minimal incremental support requirements. The majority of the costs are born by the core businesses, and therefore, at least initially, customers of the excess capacity do not need to foot the bill for capital expenditures. Costs associated with staff training, facilities, and development are similarly already fully amortized and absorbed by the parent businesses. There is little more appealing than being able to sell something that you get for free.

With such an appealing proposition in play, many other organizations are scrambling to see whether they have an infrastructure — public or private — that can be exploited for gain through cloud computing. However, when significant excess capacity does not exist, or if it cannot be leveraged in a timely or reliable fashion, it is not clear what sustainable business models exist for cloud computing.

High-end, public cloud computing offerings represent a convergence of grid and Internet technologies, potentially enabling workable new business models. Smaller, private clouds are a technical evolution that expands the ease of use and deployment of grids in more organizations.

As cloud computing technologies mature, InterSect360 Research sees several possible business models that could evolve. Although we emphasize High Performance Computing in our analysis, cloud computing transcends HPC, and similar models will exist in non-HPC markets.

Utility Computing Models

Cloud computing provides a methodology for extending utility computing access models. Utility computing is not new; it has been touted for several years as a way for users to manage peaks in demand, extend capabilities, or reduce costs. Traditionally, limitations in network bandwidth, security issues, software licensing models, and repeatability of results have acted as barriers to adoption, and all of these still need to be addressed with cloud.

There are four major variations on the potential utility computing models with cloud:

Cycles On Demand

The cycles-on-demand model is the most basic approach to cloud computing. The cloud supplier provides hardware and basic software environments, and the user provides application software, application data, and any additional middleware required. In this case users are simply buying access to computer processors, which they provision and manage as needed in order to run their applications, after which the resources are “returned” to the cloud provider. Users are charged for the time the resources are in use, plus possibly some overhead costs. The demands are relatively low on the cloud provider, and relatively high on the user in terms of making sure there is effective utility generated by the rented resources.

Storage Clouds

The storage cloud model complements the cycles-on-demand model both in terms of operational approach — users buy disk space at a cloud providers facility — and in terms of providing a more complete solution for cycles users — a place to put programs and data between job runs. In the storage-on-demand approach the cloud is used:

  • As the final (archival) stage in hierarchical storage management schemes (even if it is a two-level hierarchy: local disk and cloud). On the consumer side this is essentially the concept used for PC backup services.
     
  • A file-sharing buffer where users can place data that can be accessed at a later time by other users. This approach is at the heart of photo sharing sites, and arguably with social sites such as Facebook and LinkedIn. This same concept is also used for shared science databases in areas such as genomics and chemistry.

Software as a Service

Software as a service (SaaS) extends the basic cycles-on-demand model by providing application software within the cloud. This model addresses software licensing issues by bundling the software costs within the cloud processing costs. It also addresses software certification and results repeatability issues because the cloud provider controls both the hardware and software environment and can provide specific system images to users.

SaaS also has the advantages for providers of allowing them to sell services along with the software, and to use the cloud as demonstration platform for direct sales of software products. In addition, the user is able to turn much of the system administration task over to the provider. The major drawback to this strategy is that users generally run of a series of software packages as part of their overall R&D workflow, in such case data would need to be moved into and out of the cloud for specific stages of the workflow, or the cloud provider must support an end-to-end process.

Environment Hosting

Environmental hosting is the use of a service to support virtually all computational tasks, with servers, storage, and software all being maintained by a third party. This concept can include constructs such as platform as a service (PaaS) and infrastructure as a service (IaaS). Arguably environmental hosting in the cloud is an oxymoron, however, it represents the upper end of the utility computing spectrum and a logical destination of cloud strategies. This approach addresses software, result repeatability, and most networking issues by simply providing dedicated resources all in one (logical) place. It addresses many of the technical security issues, but not a consumer organization’s security problem of inserting a third party into the workflow process.

Cloud-Generated Markets

In addition to the models for those who would consume resources through the cloud, there are applications that are made possible by the combination of Internet communications and large computing resources. This is inclusive of the opportunities for organizations to become cloud computing service providers, either externally or internally. In addition, there is the potential for some secondary markets to be enabled by the adoption of cloud technologies.

Restructuring of Internet-Based Service Infrastructures

One of the most interesting aspects of cloud computing is that Internet companies with value-add and expertise in intellectual property or content (as opposed to purchasing, managing, and running computer hardware systems) could move their internal computing architecture to the cloud, while maintaining system management and operating control in-house. With this strategy an organization would move the bulk of its computing to the cloud keeping only what is necessary for communications and cloud management, in doing so they convert internal costs for systems, software, staff, space and power into usage fees in the cloud. Cloud technology and service providers facilitate and accelerate the industry’s evolution towards a network of interrelated specialty companies, as opposed to groups of organizations each performing the same set of infrastructure functions in house. The major issue potentially holding this model back would be cost; i.e., the level of premium users would be willing to pay for a service versus a do-it-yourself solution.

Personal Clouds

This strategy would replace personal computers with an advanced terminal that connected to a cloud utility that holds all of the user’s data and software. The advantage for users is that they would be relieved of the burden of purchasing, maintaining, and upgrading their personal systems. They would also have professional support for such task as system back-up and system security and would also be able to access their computing environment form any Web-connected device.

This strategy may represent the evolutionary future of the Internet, particularly as more devices become Web-enabled and the relationship between the Web and the personal computer is weakened by competing devices, such as smart phones. The main challenge to this model is overall bandwidth on the Internet. Side effects to such an evolution would replace the role of the operating system with a Web browser and whatever backend environment the cloud supplier chose to provide, also creating a new product class for Web terminals.

InterSect360 Research Analysis

We see cloud computing as part of the logical progression in distributed computing. It is not completely revolutionary, nor is it a panacea that will provide any service that can be imagined. The business models must be considered in terms of cost and control, barriers and benefits.

Of all the cloud business models, InterSect360 Research believes that SaaS has the highest potential for success within HPC. It addresses several of the major dampening factors associated with cloud and provides additional revenue opportunities in the services arena. It also targets industrial users, who would be the most likely to pay a premium for the product, without attempting to develop competing solutions. Furthermore companies can adopting SaaS models in cloud in a phased or tiered way, first proving the concept private clouds before giving themselves over to public or hybrid models. (This same phenomenon persists with private and public grids today.)

Organizations that have experience with the software and in house operations may look to SaaS options for peak load management and capacity extension. However, we believe the greater opportunity is for selling packaged cloud computing, software, and start-up services to companies testing HPC solutions. Our research indicates that there are major start-up barriers to using HPC solutions among small and medium companies. These barriers include finding the expertise for the creation of the organization’s first scalable digital models.

The major barrier for SaaS adoption in HPC is the fragmentation of the applications software sector of the industry. The boutique nature of the opportunity may indicate there is not sufficient volume to merit the ISV’s investment to create and market cloud-enable versions of their applications. Interestingly, in a recursive manner, small SaaS providers could theoretically tap into larger cycles-on-demand cloud providers to supply the computing resources.

Similarly, implementation of environment hosting within current cloud environments for HPC organizations would currently entail significant amounts of effort by the user organization to set up and manage storage and software environments. It would also be limited by software licensing issues for industrial users in particular. Thus market opportunities for this option are very limited at this time. That said, a small organization could conceivably do all its computing in the cloud, keeping all its data on cloud storage system, using only internally developed, open-source, or SaaS software, and trusting in small size as part of a herd to provide security.

Finally, we note that Web-based software services are not new to the market; they currently range from income tax preparation services to on-line gaming companies. SaaS fits into cloud markets based on the concept of work being sent to outside party and results returned, without the sender having knowledge of exactly how those results are generated. For some users, SaaS may inherently make sense. Ultimately the best way to help users adopt HPC applications may be to make them Somebody Else’s Problem.

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

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

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

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

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

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

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

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

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

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