Petaflops and Power Consumption

By Nicole Hemsoth

July 7, 2006

Cray recently won the world's first order for a petaflops computer, which is headed for ORNL in 2008. During the ISC2006 conference, we caught up with Steve Scott, Cray's chief technology officer, and asked for his perspective on the HPC industry's drive toward petascale computing.

HPCwire: ORNL crossed an historic milestone by placing the first petascale order, but NSF, LANL, the DARPA HPCS program and other DOE sites are also aiming for petaflops capability, along with others outside of the U.S. What brought about this strong petaflops momentum?

Scott: One important impetus in the U.S. was certainly the Earth Simulator, which sparked a lot of self-examination, a lot of concern about America's ability to maintain leadership in science and engineering. As a nation, we had been lulled into complacency by our lead in COTS-based HPC systems and were surprised by the dramatic performance lead demonstrated by the Earth Simulator on real applications.

Predictably, there was a split reaction. The defensive reaction was to dismiss the Japanese system as special purpose and therefore safe to ignore. Fortunately, more constructive assessments won out and ultimately led to a series of thoughtful reports from the HECRTF, NAS and others. These helped set the stage for the DARPA HPCS program, which embraces sustained applications performance, for the American Competitiveness Initiative and for the petascale plans within the DOE and NSF.

HPCwire: What's your take on the march toward petascale computing?

Scott: We're on the cusp of a very interesting era in high-end architecture. The single-thread juggernaut is over. We're no longer improving single-processor performance at close to historical rates. Scalability and software capability are major issues, and power consumption is another very important issue, not just for HPC but for the whole computer industry.

HPCwire: This isn't the first time I've heard someone say that. How can the HPC industry deal with the power issue?

Scott: There are two approaches. In the first, you drop the voltage and lower the frequency of individual processors, then compensate by using more processors in a system. Multi-core processors embody this approach to a moderate extent, and some special purpose designs have taken it even farther. The primary concern here is that this approach exacerbates the scaling problem. The memory wall gets worse, there's more memory contention, codes have to be more parallel, the communication-to-computation ratio gets worse, and you have to depend more on locality. This approach is very valid for certain types of applications. For highly local, partitionable applications, for example, it's a good low-power design. The more you push this concept, the more potential power savings you have, but the more special-purpose the machine becomes.

Another alternative is to design processors that have much lower control overhead and use more of their silicon area for performing computations. Streaming processors, vector processors and FPGAs are example of this approach, which can result in much faster single processors for the right types of codes, and thus ease the requirement for greater scaling. This technique can be used to a lesser extent in traditional scalar microprocessors. SSE instructions, for example, are essentially vector instructions that can increase peak performance without a corresponding increase in control complexity. On top of all this, you can also implement adaptive power-management mechanisms to reduce power consumption by idling or voltage scaling selected blocks of logic in the processor. Microprocessor vendors have a big motive to reduce power consumption because it affects their whole market, not just the relatively small HPC segment.

HPCwire: So which techniques do you think hold the most promise?

Scott: I don't think there's one right answer. Ultimately, the important thing is matching the capabilities of the machine with the needs of the applications. The variety of applications calls for a variety of solutions, each optimized for the right system balance. This will lead to more performance-efficiency and power-efficiency.

I think some processor vendors are coming to similar conclusions. AMD just rolled out an aggressive program to open up and license their coherent HyperTransport technology in order to create a heterogeneous ecosystem around the AMD Opteron processor. They're encouraging third parties to develop chips that interface with Opteron and augment Opteron in a variety of ways. AMD is not trying to keep the processor closed and do everything themselves. Cray is participating in this AMD program and leveraging it in our “Cascade” architecture.

What you don't want to do is compromise application performance. In the end, efficiency is defined by meeting the needs of the applications. There's a place for different types of processors. I'm excited because the slowdown in single-thread improvement has created an opportunity to innovate and add some very useful functionality on and around microprocessors.

HPCwire: Switching topics a bit, the Cray XT3 has been winning some big procurements recently. Why?

Scott: When they do the benchmark comparisons, customers are seeing that the Cray XT3 is a balanced system with a bandwidth-rich environment and a scalable design. It costs more on a peak flop basis, but it's more effective on challenging scientific and engineering applications and workloads. As I said earlier, clusters can often handle less-challenging applications really well.

HPCwire: What do you see when you look out ahead?

Scott: One big coming shift is that parallel processing and programming are going mainstream. In 10 years, desktop systems might have tens of processors and serial code will no longer be the answer. We really need to make parallel programming for the masses easier than our current MPI model. The HPCS program is taking an aggressive approach to this important issue by pushing for the development of new high-productivity parallel programming languages.

Another difficult issue is that Moore's Law will likely end by 2020 or soon after that, not because of power consumption but because we'll reach fundamental physical limits. We're going to need to move beyond CMOS.

HPCwire: What comes after CMOS?

Scott: It's a bit too soon to tell. Carbon nanotubes are looking promising.

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!

Intel’s Silicon Brain System a Blueprint for Future AI Computing Architectures

April 24, 2024

Intel is releasing a whole arsenal of AI chips and systems hoping something will stick in the market. Its latest entry is a neuromorphic system called Hala Point. The system includes Intel's research chip called Loihi 2, Read more…

Anders Dam Jensen on HPC Sovereignty, Sustainability, and JU Progress

April 23, 2024

The recent 2024 EuroHPC Summit meeting took place in Antwerp, with attendance substantially up since 2023 to 750 participants. HPCwire asked Intersect360 Research senior analyst Steve Conway, who closely tracks HPC, AI, Read more…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, and this day of contemplation is meant to provide all of us Read more…

Intel Announces Hala Point – World’s Largest Neuromorphic System for Sustainable AI

April 22, 2024

As we find ourselves on the brink of a technological revolution, the need for efficient and sustainable computing solutions has never been more critical.  A computer system that can mimic the way humans process and s Read more…

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

Intel’s Silicon Brain System a Blueprint for Future AI Computing Architectures

April 24, 2024

Intel is releasing a whole arsenal of AI chips and systems hoping something will stick in the market. Its latest entry is a neuromorphic system called Hala Poin Read more…

Anders Dam Jensen on HPC Sovereignty, Sustainability, and JU Progress

April 23, 2024

The recent 2024 EuroHPC Summit meeting took place in Antwerp, with attendance substantially up since 2023 to 750 participants. HPCwire asked Intersect360 Resear Read more…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips 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…

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…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia 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…

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…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t 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…

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…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E 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…

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…

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…

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…

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…

Intel’s Xeon General Manager Talks about Server Chips 

January 2, 2024

Intel is talking data-center growth and is done digging graves for its dead enterprise products, including GPUs, storage, and networking products, which fell to Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire