Anyone Know Where We’re Headed?

By Michael Feldman

April 6, 2007

One of the more exciting aspects of high performance computing today is that there is no real consensus on what it's going to look like in the next several years or how are we going to get there. Multicore/manycore seems inevitable, yet the software technology is years behind the hardware. Clusters seem unstoppable, but manycore will essentially give you a cluster on a chip. Hardware accelerators and heterogeneous computing promises the ultimate in performance and efficiency, but there's that darn problem of software again.

It would be diplomatic to say that all the different computer architectures will share a place in the future, but that's not usually the way it works out. Commodity clusters effectively killed custom processor-based supercomputers. Multicore technology sent single-core processors into the history books. Clusters and multicore processors became big at the expense of the architectures they replaced. Apparently, diversity has its limits in the marketplace.

Right now, there's a lot of architectural experimentation going on — and not just in the labs. Vendors like Sun are fielding systems based on 8-core, 32-thread processors (T1 UltraSPARC); SiCortex is using MIPS cores and a novel interconnect topology to achieve impressive performance/watt numbers; SGI, Cray and others offer FPGA acceleration with some of their systems; and Cell processors, GPU cards and ClearSpeed boards are each being incorporated into commercial HPC systems to squeeze more FLOPS out of the machines.

For the future, Intel is prototyping 80-core processors for general-purpose computing, while AMD is making plans to integrate CPUs and GPUs on the same processor die.

What will the dominant HPC architecture be in the future and how will the software adapt? Or should the question be reversed? If you wonder about such things, this issue of HPCwire is worth a read. Each of our first three feature articles talks about how HPC hardware architectures and software could move forward — or fail to do so.

Wake up and smell the software

ClearSpeed's John Gustafson pitches the idea that HPC software developers need to rethink how to code their applications for modern architectures. His article talks about the new realities that effect how software should be developed. Briefly, these realites are: processors and memory are cheap; memory bandwidth and software developers are expensive.

His contention is that, unlike in the past, it makes perfect sense to “waste” the abundant RAM and processing resources if it makes the applications more productive or just easier to program. Gustafson wonders, for example, why we obsess so much about processor utilization, instead of focusing on programmer utilization. His basic message is that we need to develop our algorithms in line with the realities of our architectures and the economics of software development.

What could be simpler?

If as Leonardo DaVinci said, “Simplicity is the ultimate sophistication,” then Jud Leonard is on the right track. Our second feature article has Leonard, co-founder and CTO of SiCortex, arguing a different line of attack than Gustafson's. Leonard contends that rather than accepting the current limitations of today's hardware, we should be simplifying the system design to address those limitations. He says that for demanding HPC codes, we still need to be concerned with hardware efficiency, and we need to ensure that legacy codes run efficiently on our future systems.

The key to his approach is to simplify the system at every level (no heterogeneity here). This includes integrating the node's processing hardware as tightly as possible, flattening the inter-node communication network, and synchronizing the clocks of all the node processors. He disparages the current trend of using desktop-derived x86 processors in HPC, noting that this architecture is not well suited to technical computing.

What he describes is all very SiCortex-y, but the broader message is about how much system architects have compromised efficiency for the advantages of using commodity parts. According to Leonard, simplifying the architecture will not only make the machines more efficient, but will also provide a friendlier, more predictable environment for parallel programming.

Putting cores to work

A kinder, gentler parallel programming model is what our third feature article is about. PGI's Michael Wolfe wonders what we're going to do with all those cores that the hardware guys keep threatening us with. Wolfe recently attended two conferences, CGO (Code Generation and Optimization) and PPoPP (Principles and Practice of Parallel Programming), where multicore and parallel programming were understandably hot topics.

The conference discussions inspired him to share a few of his thoughts about the intersection between processor architectures and programming models. Some of the areas Wolfe talks about are transactional memory, GPGPU (which he seems to be lukewarm on), and parallel programming languages. As a compiler engineer, his bit-twiddling perspective provides some interesting insights on how different software approaches might deal with the coming core-quake.

Spring Break for HPCers

Finally, I'd be remiss if I didn't point out our special coverage of the High Performance Computing & Communications Conference (HPCC), which took place in Newport, Rhode Island this week. Our Newport HPCC Conference supplement section in this week's issue has a number of feature articles on the presentations as well as some other highlights from HPCwire contributing writer John E. West, who provided live play-by-play on the proceedings. Thanks John.

The HPCC Conference is in its 21st year and has established itself as the boutique HPC conference of the spring season. It's been held in Newport for so long that people just refer to it as the Newport Conference. John Miguel, the perennial conference organizer, has been heading the event ever since its inception in the 1980s. It's not a highly technical conference, nor is there a big emphasis on exhibitors — just 16 this year. The event is more about finding out what's going on in the industry and what direction the federal government is taking with high-end computing.

“If you want a techie or trade show conference, you go to Supercomputing (SC) in November,” Miguel told me. “Ours is more like a high-level retreat than a conference.”

Every year he tells himself that maybe this will be the last conference. But people always come up to him afterwards and let him know they want to do it again next year. So as long as he can figure out how to pay for it, he says he'll keep the conference going.

—–

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!

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

Nvidia Appoints Andy Grant as EMEA Director of Supercomputing, Higher Education, and AI

March 22, 2024

Nvidia recently appointed Andy Grant as Director, Supercomputing, Higher Education, and AI for Europe, the Middle East, and Africa (EMEA). With over 25 years of high-performance computing (HPC) experience, Grant brings a Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen 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…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. 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…

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…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a 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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer 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…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire