New Center at University of Michigan Aims to Democratize the Design and Manufacturing of Next-Generation Systems

January 15, 2018

ANN ARBOR, Mich., Jan. 15, 2018 — As the computing industry struggles to maintain its historically rapid pace of innovation, a new, $32 million center based at the University of Michigan aims to streamline and democratize the design and manufacturing of next-generation computing systems.

The Center for Applications Driving Architectures, or ADA, will develop a transformative, “plug-and-play” ecosystem to encourage a flood of fresh ideas in computing frontiers such as autonomous control, robotics and machine-learning.

Today, analysts worry that the industry is stagnating, caught between physical limits to the size of silicon transistors and the skyrocketing costs and complexity of system design.

“The electronic industry is facing many challenges going forward, and we stand a much better chance of solving these problems if we can make hardware design more accessible to a large pool of talent,” said Valeria Bertacco, an Arthur F. Thurnau professor of computer science and engineering at U-M and director of the ADA Center.  “We want to make it possible for anyone with motivation and a good idea to build novel high-performance computing systems.”

The center is a five-year project that’s led by U-M and includes researchers from a total of seven universities, pending final contracts: Harvard University, MIT, Stanford University, Princeton University, University of Illinois and University of Washington.

ADA is funded by a consortium that is led by the Semiconductor Research Corporation and includes the Defense Advanced Research Projects Agency. The center is one of six new centers recently announced as part of the Joint University Microelectronics Program, organized by the Semiconductor Research Corporation.

ADA aims to democratize the development and deployment of advanced computing systems in several ways: It will develop a modular approach to system hardware and software design, where applications’ internal algorithms are mapped to highly efficient and reusable accelerated hardware components. This faster and more effective approach will require that the entire design framework—from system software to architecture to design tools—be reimagined and rebuilt.

“You shouldn’t need a Ph.D. to design new computing systems,” Bertacco said. “Five years from now, I’d like to see freshly minted college grads doing hardware startups.”

Computing has had a monumental impact on society, but the path forward is uncertain. Researchers are looking for creative approaches to extend the utility of traditional silicon beyond the Moore’s Law era, a long-standing but waning trend in which chips become cheaper to manufacture, and more powerful, each year.

ADA researchers see customized silicon for specific applications—like chips optimized for image search or data analytics—as a promising approach. But the biggest industrial customized silicon successes to date, such as smartphone systems-on-a-chip or graphics processing units, have required the immense resources of large, deeply integrated, vertical design teams. ADA’s goal is to change that. The center is organized into three themes:

Agile system development: The team will identify patterns in the core algorithms of emerging applications—such as virtual reality, machine learning and augmented reality—in order to map those algorithms to new, tailored computational blocks.This approach would slash design costs by building ready-to-use components that usher designs all the way from high-level computational languages to fully packaged systems.

Algorithms-driven architectures: The researchers will develop reusable, highly efficient algorithmic hardware accelerators for the computational blocks. Instead of targeting the application itself, designs will target the underlying algorithms. Special-purpose hardware designs can improve the efficiency-per-operation by several orders of magnitude over a general-purpose chip. Such special-purpose hardware design occurs today, but it can take a decade after a need is identified before mature and efficient solutions are available, and it requires extremely specialized expertise, the researchers say.

Technology-driven systems: A key aspect of this theme involves developing an open-source chip scaffold for these new, accelerator-centric systems. The scaffolds would include all the necessary support subsystems—such as general-purpose cores, on-chip communication fabric, and memories—to facilitate a “plug-and-play” flow. “One will no longer need to send a design to the fab and wait for a chip to come back. They may still need a clean room to assemble a system, but this will be much simpler and more economical,” Bertacco said. Researchers will also explore technology innovations independent of silicon scaling.

“This is a daring and progressive approach to system design that stands to revolutionize the computing industry,” said Alec Gallimore, who is the Robert J. Vlasic Dean of Engineering, the Richard F. and Eleanor A. Towner Professor, an Arthur F. Thurnau Professor, and a professor both of aerospace engineering and of applied physics. “The work of this new center will empower generations of engineers and computer scientists to design and build the systems that can bring their ideas to life.”

DARPA and the Semiconductor Research Corporation will contribute $27.5 million to this project, with the remaining funds provided by the participating institutions. The Semiconductor Research Corporation is a global, high technology-based consortium that serves as a crossroads of collaboration between technology companies, academia, government agencies, and SRC’s engineers and scientists.


Source: University of Michigan

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!

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…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t 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 of Rigetti’s Novera 9-qubit QPU. The approach by a quantum Read more…

2024 Winter Classic: Meet Team Morehouse

April 17, 2024

Morehouse College? The university is well-known for their long list of illustrious graduates, the rigor of their academics, and the quality of the instruction. They were one of the first schools to sign up for the Winter 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…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it 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…

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…

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…

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…

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…

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…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire