The HPC to Enterprise Infrastructure Leap

By Nicole Hemsoth

February 24, 2014

As more companies feel the burdens of growing data demands in terms of volume and complexity—not to mention the need to derive results on such data quickly and efficiently—the chasm between what was once considered mainstream enterprise computing and “traditional” high performance computing is  is narrowing.

As we’ve addressed in other parts of this special series on lessons that HPC can carry into a growing array of enterprise application areas, including those that have a range of defined “big data” problems, this merging of HPC and commercial computing has been underway with increasing veracity over the last few years in particular—directly in line with momentum around the many data movement, ingestion and processing, memory, efficiency and other challenges enterprise users face.

While HPC has always had a foothold in key commercial segments (financial services, oil and gas, government, etc.) the technologies that were once reserved for these large-scale commercial areas are filtering down to a wider base of existing enterprise entities. It’s not uncommon lately (in the wake of the hubbub around big data) to hear about insurance companies, web retailers, content and media companies and others taking notice of HPC technologies in new ways.  Bill Mannel, General Manager of Compute Servers at SGI echoed this following a conversation about this HPC to enterprise leap, noting, “Key lessons that commercial and enterprise datacenters can take away from HPC is that infrastructure matters based upon your application, your data, and the quality of service expectations of customers.”

While many won’t disagree with that point, for those with complex applications, infrastructure has to matter in different ways than it used to. As Cray’s VP of Storage and Data Management, Barry Bolding told us, one of the most important lessons for the commercial segments is productive scalability. “The commercial/enterprise space understands productive virtualization, which is a type of scaling that improves utilization of resources. The area of productive scaling that HPC brings to the table is efficient, productive scalability for complex systems.  Scaling to fit an HPC solution in the coming years will require efficient parallel computing (both HW and SW), efficient parallel storage (to ensure no data access bottlenecks) and scalable analytics.

Bolding says the enterprise is seeing more and more applications needs that fit this model of parallel compute, storage and analytics.  The energy sector is using new, complex algorithms to do oil and gas exploration and productive scalability is key to meeting their needs.  In this example parallel, scalable storage and compute are the core to solving the problems efficiently.

Another key lesson that HPC can bring to bear is adaptive technologies, he says, noting that “for maximum efficiency and TCO it is critical to match the application need to the appropriate underlying technology. This is contrary to the cloud model where little effort is made to match the underlying technology to the application.”

When asked about the infrastructure leap from HPC to enterprise, Paul Dlugosch of Micron explained that “It is the HPC industry that first meets the most critical and difficult problems encountered in scientific and technical computing and it is true that innovations in the HPC industry often trickle down into mainstream use in commercial/enterprise datacenters.” In some cases, he says, the innovations can migrate all the way down to the client or consumer space.” In short, although the HPC industry operates at the top of this hierarchy of compute capability, there are “lessons learned in the HPC industry that have practical application throughout the entire spectrum of compute capability.”

While performance remains an important metric, Dlugosch says a myopic focus on performance can lead towards the top of a pyramid where the performance crown may be acquired but the overall market for the technology developed might becomes proportionately smaller. “When performance is the only objective, important opportunities may be missed. A good example would be the disruption imparted on high performance microprocessor vendors by the emerging need for lower power processors where less compute performance was an acceptable trade off. The lesson here, of course, is that focus on high performance may miss very important innovations that are not based on processing performance.”

Performance does indeed drive all aspects of the computing industry, but a sole focus on compute performance can leave a business vulnerable, argues Dlugosch. While the HPC industry can better afford a concentrated focus on compute performance, this does not extend to other segments of the computing industry where performance is only one of several metrics that will determine overall success.

One other area where HPC and enterprise users can connect is in the realm of risk adversity, says Dlugosch. As he explained in a detailed interview:

The old adage that ‘nobody ever got fired for buying IBM’ reflects this point quite well.  Of course, IBM in this case is a proxy for any well established, mature and stable technology provider.  While it may be true that nobody gets fired for buying tried and true technology, entire businesses can fail because they did not recognize important technology inflection points that were coming their way.  There are many popular examples that include Wang Computer (client based word processing), Digital Equipment (personal computer) among others.

The HPC industry is quite used to operating in the domain where the opportunity for failure is high.  It is the nature of pushing the boundaries of computing capability.  So what lesson might the commercial/enterprise data centers learn for the HPC community in this respect?  You must be willing to explore technologies outside the comfort zone defined by incremental or evolutionary improvements.  Customers have a long history of driving suppliers and service providers along predictable paths of incremental improvements.  

While this may be safe and meet the needs of the immediate business, following this safe path may lead to a missed opportunities afforded by new and emerging technologies.  In particular, low end disruptions enabled by new technologies can be detrimental to businesses that are caught off guard.  While the HPC industry is naturally focused on the high end of the computing spectrum and have a higher tolerance for risk, commercial/enterprise data centers must also take ownership for innovation and not assume it will come from their technology providers or through customer demands.

The problem of choosing the proper system for a given workload is not just an HPC issue. However, according to some, including Bill Dunmire, Senior Director of Product Marketing at SGI, “High performance computing is generally unchartered territory within enterprise data centers. It is here that “clusters” are utilized for HA (server failover) or server virtualization (e.g. V-motion) as opposed to parallel computing. Shared-memory systems are completely unknown.” He notes that in such cases, “IT will be required to develop expertise in HPC and will need to avoid inefficiencies in performance, scalability, and cost as LOB demands grow.”

Add to that general view, the more complex matters of system design and architecture which, as Jack Dongarra of Oak Ridge National Lab and the University of Tennessee told us, leads traditional HPC and enterprise users of advanced computing to two key questions—first, how can/should the internal architecture of HPC systems be changed to make them more suitable for data driven commercial applications? Second, how can/should external storage systems and their interfaces be adapted in order to efficiently orchestrate, as part of the overall workflow, the movement of data into and out of these systems? At this point in time, however, these questions seem to only generate more questions rather than any widely accepted (or even plausible) answers.

“Issues of interoperability are closely related with fundamental questions about the architecture and codesign of hardware and software infrastructure,” Dongarra explained. “Unfortunately, these same factors tend to make them relatively intractable. For interoperability has to mean more than just “everyone adopts the same standard or the same interface.” Aside from cases where de facto or de jure monopoly power is exercised, a viable approach to interoperability for infrastructure means designing protocols and interfaces that people voluntarily adopt because they can use them to achieve their functional goals while also achieving deployment scalability and sustainability over time.”

Echoing Jack Dongarra’s questions and potential roadblocks to widespread changes in enterprise computing, HPC researcher, Dr. Kirk Cameron of Virginia Tech explained that “The problems of scalability, speed, and complexity manifest acutely at the extreme scales that challenge the HPC community daily. Thus, the incessant need in HPC to maintain competitiveness by pushing simulation fidelity and scale to solve problems of grand importance to a myriad of sciences ensures the rapid adoption of cutting edge technologies.” He points to certain technologies, such as the Cell Broadband Engine, are vetted and then only briefly embraced by commercial enterprises. Other technologies, such as general purpose graphics processing units (GPGPUs), are vetted and ultimately adapted and integrated into the mainstream as evidenced by Intel and AMD embracing systems-on-chip technologies with GPGPUs built in. Much like high-performance car racing drives advances in automobile efficiency, HPC pushes the limits of computing so that commerical/enterprise datacenters can adopt best-in-class techniques and technologies to reduce the burden on their in-house R&D efforts.”

The central question is which technologies will enterprises seek and adopt that filter from HPC, especially with some of the potential barriers Dongarra and others have mentioned. To arrive at a more thorough answer to that question, we’ll be exploring a few aspects of these topics in coming special sections in the HPC to enterprise series around accelerators, HPC clouds and overall workflow/software issues later this week.

 

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 Update: Interview 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 Update: Interview 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

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