A Plateau of Productivity for Grids

By Nicole Hemsoth

May 23, 2011

Last October a study from Platform Computing, SAS, and the TABB Group pointed to a coming explosion in the use of cloud, cluster and grid technologies in financial services due to the rapidly rising river of data and need for scalable compute to manage it.

This study revealed that a majority of financial institutions hoped to combine grid and cloud technologies with 53 percent considering investments in grid computing in the next two years and 57 percent looking into the possibilities of cloud computing.

While this shows that grid computing models are alive and well in this particular industry (which has been making use of grids for many years now) it is only recently that grids are “growing up” say the authors of a detailed report from consulting firm Excelian.

The authors behind the Excelian report suggest that for financial services users, “at its best, grid is being used as an enterprise level large-scale distributed compute solution and at its least effective, it is seen purely as a point solution for parallel compute.” They suggest that we are at a point where the ecosystem has matured enough for us to determine these larger trends and look ahead to ways to build on grid successes.

Excelian’s report makes the claim that following several years of growth, this year marks the “plateau of productivity for grid” and urge financial services companies to step back and take stock of their progress on grid computing solutions.

The bedrock under this plateau of grid computing productivity has to do with the movement from this computing model from less of a specialist technology to more of a commodity, according to Dr. Adam Vile, one of the lead authors of the Excelian report.  He further explains this concept, which is embodied by the “Grid Grows Up” title of the study, noting that this movement from specialization to commoditization simply means that when it comes to grids, the mystery is gone. He told us that these days, “grid specialists are not so much in demand and almost every bank has one. There is an understanding about how to program for, deploy and manage grid that has grown up over the last 10 years. Furthermore, vendor products are mature and are managing grids of tens of thousands of nodes.”

Vile went on to explain that “grid management is moving to an operational phase, and we are seeing infrastructure or middleware groups running grids now rather than more specialist application developer groups.  Grid evolution is paralleled in examples of message bus or the database, and is becoming a well understood service rather than a specialist black box.”

Although financial services might need to reevaluate their distributed computing solutions at the moment, the report does indicate that grids are uniquely suited to the banking market in particular due to scalability and management ease as well as the ability to use a variety of operating systems, however these are some of the same arguments made in favor of enterprise use of cloud computing resources.

According to Vile, grid computing has a unique meaning for financial services companies due to their need to provision large-scale distributed environments to manage calculations within strict service levels. He explained that for grids in this industry, the vision of it as a ubiquitous, shared compute resource isn’t on the top of the financial services agenda—rather the key lies in the ability to share internally.

Given the focus on scalability, management and operating system diversity when it comes to grid value in financial services, one could propose that these are similar points of interest for enterprise users in any industry considering cloud computing. It can be difficult to draw the line between what is more valuable for financial services companies on the grid-cloud line, which Vile notes is a frequent matter of debate. In his view, the lines between grids and clouds are blending in the research community whereas in the industry they are still highly distinct, especially since the main goal for grids in the financial services industry is to manage the completion of required work in a certain allotted period of time.

He further explained this division, noting that “typically grid uses a set of allocated machines and cores, certainly in production environments, to guarantee service levels. Cloud is seen as a mechanism for providing resources on a more flexible basis–internal or external (notwithstanding the challenges of security, latency and service levels) and is more pervasive than the provision of compute.” He says due to these differences, he has seen banks interested in using cloud to drive up utilization in their server estates through the matching of workloads use patterns outside of compute oriented workloads, and that they do see interest in using cloud externally as a “burst” capacity.

He says that beyond this, financial services companies can look at different ways to manage their current computing resources and maximize what they do have.

“Point solutions are inefficient uses of expensive commodity technology and costs are, as ever, under scrutiny in the financial services industry. A number of our customers and clients have grown their grids from a technology that creates new business into a service necessary to do business; some are just starting out on the grid journey. We felt than now was a good time to look at the industry and the use of grid and help people understand that as the technology matures the challenges change, and to position themselves in terms of a routemap for grid assimilation.”

Vile points out that the grids are, of course, not a new concept but its organic growth has pushed many organizations to consider more thoroughly how they can be used and managed.

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!

Study Identifies Best Practices for Public-Private HPC Engagement

August 22, 2017

What's the best way for HPC centers in the public sphere to engage with private industry partners to boost the competitiveness of the companies and the larger communities? That question is at the heart of a new study pub Read more…

By Tiffany Trader

Google Launches Site to Share its NYC-based Algorithm Research

August 22, 2017

Much of Google’s algorithm development occurs in groups scattered throughout New York City. Yesterday, Google launched a single website - NYC Algorithms and Optimization Team page - to provide a deeper view into all of Read more…

By John Russell

Dell Strikes Reseller Deal with Atos; Supplants SGI

August 22, 2017

Dell EMC and Atos announced a reseller deal today in which Dell will offer Atos’ high-end 8- and 16-socket Bullion servers. Some move from Dell had been expected following Hewlett Packard Enterprise’s purchase of SGI Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Glimpses of Today’s Total Solar Eclipse

August 21, 2017

Here are a few arresting images posted by NASA of today’s total solar eclipse. Such astronomical events have always captured our imagination and it’s not hard to understand why such occurrences were often greeted wit Read more…

By John Russell

Study Identifies Best Practices for Public-Private HPC Engagement

August 22, 2017

What's the best way for HPC centers in the public sphere to engage with private industry partners to boost the competitiveness of the companies and the larger c Read more…

By Tiffany Trader

Tech Giants Outline Battle Plans for Future HPC Market

August 21, 2017

Four companies engaged in a cage fight for leadership in the emerging HPC market of the 2020s are, despite deep differences in some areas, in violent agreement Read more…

By Doug Black

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. 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. Just how close real-wo Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

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 a Read more…

By Tiffany Trader

Leading Solution Providers

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the 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 cam 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

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

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