The New HPC

By Michael Feldman

January 19, 2007

With this week's announcement of the reorganization and expansion of Tabor Communications, HPCwire and our sister publication, GRIDtoday, will begin to offer a broader view of the high performance computing and Grid domains, respectively. By recognizing that computing productivity is now the most important aspect in IT, the industry has begun to look at ways to identify it, measure it and improve it. Our new company-wide focus on High Productivity Computing means that HPCwire will be providing news and analysis of the “old” high performance computing community from an expanded perspective.

That's going to make my job a bit more complex. Unlike simple computing metrics like SPEC or Linpack benchmarks; network measurements of bandwidth and latency; or storage measurements of capacity and data transfer rates; productivity is notoriously hard to quantify. It's one of those things that people think “I know it when I see it,” but it's difficult to measure.

The economic definition of productivity is the amount of output created per unit input used. In computing systems, the outputs would be the useful calculations, but the inputs are more numerous and complex. Software development, computers, networks, external storage, energy consumption, physical infrastructure and maintenance define a whole assortment of input parameters. The interaction between all these elements creates a number of challenges. For example, a high performing computer combined with low performing external storage running an I/O-intensive application will probably waste most of its computational speed waiting for disk transfers to complete. Another part of the productivity puzzle is wrapped up in intangibles like the usability of the software development environment. So it's not enough to simply add up the costs of the individual pieces of a system.

Maybe a more useful way to think about computing productivity is as a combination of a system's performance, programmability, portability, reliability, and application workloads. And in fact these are the main criteria that were defined in DARPA's High Performance Productivity Systems (HPCS) program, which is tasked to develop the next-generation petascale computing systems. One of the main goals of this program is to develop technologies that will result in a 10X improvement in productivity. It's generally understood that this is the most important (and ambitious) goal of the program and is significantly more challenging than just achieving peak petaflops.

In the November 2006 issue of CTWatch Quarterly, which was entirely devoted to the issue of high productivity computing, authors Declan Murphy, Thomas Nash and Lawrence Votta, Jr. from Sun Microsystems and Jeremy Kepner from MIT Lincoln Laboratory described a quantitative productivity framework for high performance computing.

In the article titled “A System-wide Productivity Figure of Merit,” the authors summarize the challenge: “Establishing a single, reasonably objective and quantitative framework to compare competing high productivity computing systems has been difficult to accomplish. There are many reasons for this, not the least of which is the inevitable subjective component of the concept of productivity. Compounding the difficulty, there are many elements that make up productivity and these are weighted and interrelated differently in the wide range of contexts into which a computer may be placed.”

By starting with the relationship “productivity = utility/cost” and then decomposing utility into a number of relatively independent factors, the authors construct the framework: “In a well-balanced HPCS, significant costs will be incurred for resources other than just the CPU cycles that dominate thinking in the commodity cluster architectures. In particular, memory and bandwidth resources will have cost as much or more than CPU, and efficient programs and job allocation will have to optimize use of memory and bandwidth resources as much as CPU. Our framework allows for the inclusion of any set of significantly costly resources.”

In another article in the same CTWatch issue titled “Making the Business Case for High Performance Computing: A Benefit-Cost Analysis Methodology,” Suzy Tichenor of the Council on Competitiveness and Albert Reuther from the MIT Lincoln Laboratory developed a model that attempts to predict the return on investment (ROI) of high performance computing using a benefits-cost calculation.

Tichenor and Reuther explain: “Traditionally, HPC systems have been valued according to how fully they are utilized (i.e., the aggregate percentage of time that each of the processors of the HPC system is busy); but this valuation method treats all problems equally and does not give adequate weight to the problems that are most important to the organization. With no ability to properly assess problems having the greatest potential for driving innovation and competitive advantage, organizations risk purchasing inadequate HPC systems or, in some cases, foregoing purchases altogether because they cannot be satisfactorily justified.”

Tichenor and Reuther argue that business HPC adoption is being held back at least in part because end users focus on the costs (easy to measure) rather than the benefits (hard to measure). Certainly the economic case for more widespread use of high performance computing in the private sector would be strengthened if users had some tools to measure HPC value.

The most compelling reason to focus on productivity is to improve it. As we enter the petascale era, the gap between system peak performance and system utilization will continue to widen unless the HPC community starts to design and program these machines rather differently. With computing performance accelerating away from memory bandwidth and multi-core architectures racing ahead of application concurrency, the imbalances that already exist in our terascale systems are going to become even more severe. These escalating problems have been described from different perspectives: as a multi-core crisis, as a datacenter power/cooling crisis, and as a software crisis. But more generally, the current dilemma in high performance computing is a crisis of productivity.

End users will always be interested in the cost-effectiveness of developing, running and maintaining their applications. But this requires more than just studying some bullet points on a marketing brochure detailing gigaflops, gigabytes, and gigabits per second. By recognizing that time-to-market (or time-to-solution), total cost of ownership and ROI are functions of productivity rather than just raw hardware performance, the industry is realizing that a more sophisticated model for evaluating computing systems is going to be required.

—–

As always, comments about HPCwire are welcomed and encouraged. Write to me, Michael Feldman, at [email protected].

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

ISC 2024 Takeaways: Love for Top500, Extending HPC Systems, and Media Bashing

May 23, 2024

The ISC High Performance show is typically about time-to-science, but breakout sessions also focused on Europe's tech sovereignty, server infrastructure, storage, throughput, and new computing technologies. This round Read more…

HPC Pioneer Gordon Bell Passed Away

May 22, 2024

Legendary computer scientist Gordon Bell passed away last Friday at his home in Coronado, CA. He was 89. The New York Times has a nice tribute piece. A long-time pioneer with Digital Equipment Corp, he pushed hard for de Read more…

ISC 2024 — A Few Quantum Gems and Slides from a Packed QC Agenda

May 22, 2024

If you were looking for quantum computing content, ISC 2024 was a good place to be last week — there were around 20 quantum computing related sessions. QC even earned a slide in Kathy Yelick’s opening keynote — Bey Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Core42 Is Building Its 172 Million-core AI Supercomputer in Texas

May 20, 2024

UAE-based Core42 is building an AI supercomputer with 172 million cores which will become operational later this year. The system, Condor Galaxy 3, was announced earlier this year and will have 192 nodes with Cerebras Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's latest weapon in the AI battle with GPU maker Nvidia and clou Read more…

ISC 2024 Takeaways: Love for Top500, Extending HPC Systems, and Media Bashing

May 23, 2024

The ISC High Performance show is typically about time-to-science, but breakout sessions also focused on Europe's tech sovereignty, server infrastructure, storag Read more…

ISC 2024 — A Few Quantum Gems and Slides from a Packed QC Agenda

May 22, 2024

If you were looking for quantum computing content, ISC 2024 was a good place to be last week — there were around 20 quantum computing related sessions. QC eve Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of Read more…

The Future of AI in Science

May 15, 2024

AI is one of the most transformative and valuable scientific tools ever developed. By harnessing vast amounts of data and computational power, AI systems can un Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

ISC 2024 Keynote: High-precision Computing Will Be a Foundation for AI Models

May 15, 2024

Some scientific computing applications cannot sacrifice accuracy and will always require high-precision computing. Therefore, conventional high-performance c Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Leading Solution Providers

Contributors

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

Intel Plans Falcon Shores 2 GPU Supercomputing Chip for 2026  

August 8, 2023

Intel is planning to onboard a new version of the Falcon Shores chip in 2026, which is code-named Falcon Shores 2. The new product was announced by CEO Pat Gel Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

How the Chip Industry is Helping a Battery Company

May 8, 2024

Chip companies, once seen as engineering pure plays, are now at the center of geopolitical intrigue. Chip manufacturing firms, especially TSMC and Intel, have b Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire