How the US Could Achieve Superconducting Supercomputing in Five Years

By Tiffany Trader

December 9, 2014

The Intelligence Advanced Research Projects Activity (IARPA) has officially commenced a multi-year research effort to develop a superconducting computer as a long-term solution to the power, cooling and space constraints that afflict modern high-performance computing. First revealed in February 2013, when the agency put out a call for proposals, the Cryogenic Computer Complexity (C3) program aims to pave the way for a new generation of superconducting supercomputers that are far more energy efficient than machines based on complementary metal oxide semiconductor (CMOS) technology.

Studies indicate the technology, which uses low temperatures in the 4-10 kelvin range to enable information to be transmitted with minimal energy loss, could yield one-petaflop systems that use just 25 kW and 100 petaflop systems that operate at 200 kW, including the cryogenic cooler. Compare this to the current greenest system, the L-CSC supercomputer from the GSI Helmholtz Center, which achieved 5.27 gigaflops-per-watt on the most-recent Green500 list. If scaled linearly to an exaflop supercomputing system, it would consume about 190 megawatts (MW), still quite a bit short of DARPA targets, which range from 20MW to 67MW.IARPA C3 program performance projections

The C3 project, which recently awarded an unspecified amount of funding to vendors IBM, Raytheon-BBN and Northrop Grumman Corporation, will focus on developing and integrating superconducting logic with new kinds of cryogenic memory as the basis for a small-scale working model of a superconducting computer. Superconducting circuit fabrication will be provided by MIT Lincoln Laboratory and independent test and evaluation will be carried out by NIST, Boulder.

Funding high-risk/high-payoff research in support of national intelligence is IARPA’s speciality, and superconducting computing is seen as a serious post-silicon contender for HPC, according to C3 Program Manager Dr. Marc Manheimer, who was interviewed for this piece. A long-time laboratory physicist with expertise in superconducting and in cryogenic magnetic phenomena, Dr. Manheimer provided additional details about the state of the technology and the scope of the program.

HPCwire: You’ve written about the promise of superconducting and cryogenic technologies to address the space and energy challenges of traditional silicon-based supercomputing. How tractable a problem is superconducting supercomputing?

Dr. Manheimer: IARPA only takes on the hardest problems, so it’s a serious technical challenge, but we think we have a path forward to solve all of the challenges associated with superconducting supercomputing. In particular, the challenge that I see as the hardest is to develop high-density, high-efficiency, low-latency, cryogenic memory.

HPCwire: More so than the logic?

Dr. Manheimer: The logic has been around in primitive forms for about 25-30 years, and a number of primitive circuits have been fabricated and tested, so we think we can move forward with the logic in a pretty straight-forward manner. We’ve developed a fabrication facility at the Lincoln Laboratory, and we’re upgrading that so that fab can produce circuits at the level that we need to prove out this technology. On the other hand, these cryogenic memory ideas – the other half of the program – are very new, and are for the most part untested, and we will have to go through developing the basic memory cells and put them into an array and drive them and control them in a pretty short time frame as compared with typical technology development.

HPCwire: The release put out by IARPA mentions the program would be carried out in two stages: components development for the memory and logic subsystems, then integration. Is the roadmap still following the three year plus two year split outlined last year?

Dr. Manheimer: Yes, for the first three years, the logic people have to produce some key demonstration circuits and the memory people have to produce a small-scale but complete memory, including decoders and drivers, and we also need the performers to develop a plan for how they are going to integrate these. That’s the first stage. Then we’ll have another call for proposals for the second stage.

HPCwire: So the three vendors that were awarded funding, are these first-phase partners?

Dr. Manheimer: These are independent projects. Northrup Grumman has two projects that they’ve succeeded in getting funding for. One is a logic program and one is a memory program. The Raytheon Corporation is running a memory program, and the IBM Corporation is running a logic program. So there are two logic projects and two memory projects.

HPCwire: The release also mentioned standard benchmarking programs…can you tell me more about these?

Dr. Manheimer: We’re developing a prototype, a small-scale computer, and we’re going to have to figure out what applications it’s suitable for as we scale it up. We’re going to be talking to a variety of customers with a variety of application types and we’re going to have our customers develop programs that they think will be useful in telling them what the potential of superconducting supercomputing computing is to their applications.

HPCwire: How different of an ecosystem is this compared to traditional silicon-based CMOS?

Dr. Manheimer: What we’re planning to do is reuse programs so we can use standard software, but one of the things that is missing from our ecosystem that is readily available in the semiconducting system is the development software suite. Right now if you want to develop a superconducting logic circuit of any scale, you pretty much have to do it on your own. There is no Mentor Graphics program, for example, available for superconducting computing.

HPCwire: Is IARPA thinking about specific applications yet and is this a general purpose system?

Dr. Manheimer: For now, we’re thinking general-purpose computing and we’ll see what develops in the next few years.

HPCwire: Do you think superconducting logic will be the main successor to silicon-based CMOS or is it more likely that we will have multiple computing device-level technologies that will evolve to fill this gap?

Dr. Manheimer: For high-performance computing, I think superconducting supercomputing has a high probability of being the winner. For smaller scale applications, I think CMOS will be perfectly fine for providing general-purpose computing for almost everyone. Clearly, superconducting computing won’t be useful for any portable format. Everyone will be carrying around his or her own cryogenic cooler…no, that’s not going to happen, so CMOS will be around for a long time.

HPCwire: Speaking of cryo-coolers, how much space do they take up?

Dr. Manheimer: Not much, I did a comparison between Titan at Oak Ridge and a projection of our superconducting technology, and we think that including the cryo-cooler, our supercomputer will take up about one-twentieth of the floor space, and that doesn’t include Titan’s cooling system.

HPCwire: Moving over to performance, what kind of performance goals have you set for the project and in what kind of timeframe? Is it possible to get to exascale and beyond with this technology?

Dr. Manheimer: We’ve only set goals for the C3 program, and we hope to be able to judge from the C3 program results how scalable the technology is. But we have very specific energy goals in mind for C3 and throughput goals, which are hosted on the website [and depicted below]. There are two things that we have to learn from C3. The first is whether you can actually build a supercomputer based on this technology if you really wanted to, and second do you really want to? Is it going to be prohibitively expensive and is the amount of technology required going to be too high with just no clear path forward? So those are questions that we have to seriously address at the end of C3.

IARPA C3 program diagram

HPCwire: Any estimate as to how much it will cost to build the world’s first superconducting supercomputer?

Dr. Manheimer: Not really, but if you look at conventional CMOS computers, these big supercomputers take several hundred million dollars.

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