NSF Announces New Expeditions in Computing Awards

March 25, 2020

March 25, 2020 — More than a decade ago, the National Science Foundation’s Directorate for Computer and Information Science and Engineering (CISE) established the Expeditions in Computing (Expeditions) program to build on past successes and provide the CISE research and education community with the opportunity to pursue ambitious, fundamental research agendas that would define the future the field for many years to come. Funded at levels up to $10 million for five years, Expeditions projects have represented the largest single research investments made by CISE during this period. Together with the Science and Technology Centers and the National Artificial Intelligence Research Institutes that CISE now supports, Expeditions projects form the centerpiece of the directorate’s center-scale award portfolio.

“For over 10 years, the Expeditions in Computing program has harnessed the vast amount of creativity in the computer science research community to expand our field’s horizons, offer societal benefits and enhance our nation’s economy,” said Margaret Martonosi, NSF Assistant Director for Computer and Information Science and Engineering. “The projects being awarded this year will undoubtedly do the same for decades to come, pushing the boundaries on challenging research problems with the potential to yield tremendous technological and societal advances.”

Previous Expeditions awards covered an expansive breadth of topics, from synthetic biology and behavioral neuroscience to computer vision, robotics, and quantum computing. This year, three more awards are added to the portfolio. These projects have the potential for far-reaching and enduring impacts to advance core science and engineering principles across multiple domains, build and motivate new techniques and tools, and create significant societal value.

Global Pervasive Computational Epidemiology
Lead PI: Madhav Maranthe, University of Virginia.
Collaborators: Princeton University, Massachusetts Institute of Technology, Arizona State University, Indiana University, Virginia Tech, University of Maryland, Yale University, Stanford University and Center for Disease Dynamics, Economics and Policy

Infectious diseases cause more than 13 million deaths per year worldwide. Emerging trends in globalization, anti-microbial resistance, urbanization and ecological pressures have increased the risk of a global pandemic. The current coronavirus outbreak and its potential global social, health and economic implications serves as a sobering example of the problem the human race continues to face. Computation and data science can capture the complexities underlying these disease determinants and revolutionize real-time epidemiology — leading to fundamentally new ways to reduce the global burden of infectious diseases that has plagued humanity for thousands of years. This Expeditions project will enable novel implementations of global infectious disease computational epidemiology by advancing innovative computing and data science techniques. The multidisciplinary team aims to leverage tools from computational theory, artificial intelligence, machine learning and social sciences to simulate epidemics and social interactions that may control or contribute to these epidemics. The tools developed through this project could provide new analytical capabilities to decision makers, potentially improving science-based decision making for epidemic planning and response.

Understanding the World Through Code
Lead PI: Armandao Solar-Lezama, Massachusetts Institute of Technology
Collaborators: University of Pennsylvania, California Institute of Technology, Rice University, University of Texas, Austin and Stanford University

In almost every field of science, it is now possible to capture large amounts of data. This has led machine learning to play an increasingly important role in scientific discovery, for example, sifting through large amounts of data to identify interesting events. But modern machine learning techniques are less well suited for the critical tasks of devising hypotheses consistent with the data or imagining new experiments to test those hypotheses. This Expeditions award aims to develop new learning techniques that can help automate the process of generating scientific theories from data. In effect, the project team seeks to develop learning techniques that can produce models in code that look much more like the models that scientists already write by hand. The team has grounded its work in four research areas with potential for significant impact: organic chemistry, biochemistry, cognitive science and behavioral modeling, and computing systems. Machine learning is already demonstrating value in all of these domains, including predicting properties of organic compounds, recognizing complex social activities and modeling computer performance. However, the team’s techniques could have a transformative impact in all of these domains by helping scientists move from black-box predictions to a deeper understanding of the processes that give rise to the data. This project holds promise to discover the understanding of the complex processes involved in many real-world application domains that give rise to data. This deeper understanding could lead to important contributions ranging from more efficient drug discovery to improved teaching methods grounded on a better understanding of cognition.

Coherent Ising Machines (CIMs)
Lead PI: Hideo Mabuchi, Stanford University
Collaborators: Caltech, Cornell University, Universities Space Research Association

From minimizing costs to maximizing efficiency, formulating a hard problem using an optimization framework is an approach used often in computation. However, solutions to most optimization problems often take exponentially more time to solve as the problem size increases. Efficient algorithms and specialized techniques to address these challenges is therefore crucial for application domains ranging from logistics and robotics to materials engineering and drug design. This Expeditions award exploits unconventional computing architectures, called Coherent Ising Machines (CIMs), to solve a class of optimization problems. CIMs provide a platform to test ideas for computer engineering in the post-Moore’s Law era. Next-generation CIMs also hold great promise to drive substantial practical advances in artificial intelligence (AI) capabilities in multiple fields. In addition, the unconventional memory format used by these machines may establish a pathway towards novel quantum information technologies.

“These three awards will enrich CISE’s Expeditions portfolio,” said Mitra Basu, lead program director for Expeditions. “The proposed research is foundational yet tackles cutting-edge topics. The projects will tackle some of the most vexing optimization problems, address a pressing need facing society and revolutionize scientific discovery.”

About The National Science Foundation

The National Science Foundation (NSF) is an independent federal agency that supports fundamental research and education across all fields of science and engineering. In fiscal year (FY) 2019, its budget is $8.1 billion. NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and other institutions. Each year, NSF receives more than 50,000 competitive proposals for funding and makes about 12,000 new funding awards.


Source: The National Science Foundation

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!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues 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 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…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion 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…

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