Exploratory Research for Extreme-Scale Science (EXPRESS)

Abstract

FOA 24-3300: Funding opportunity solicitation in the EXPRESS program; $10.8 million over 2 years (FY24-26); Lead PM Kalyan Perumalla

Awards

Solicitation PDF

Selected Pages

Selected Extracts

Extreme-scale science recognizes that disruptive technology changes are occurring across science applications, algorithms, computer architectures and ecosystems. Recent reports point to emerging trends and advances in high-end computing, massive datasets, visualization, and artificial intelligence on increasingly heterogeneous architectures. Significant innovation will be required in the development of effective paradigms and approaches for realizing the full potential of scientific computing from emerging technologies. Proposed research should not focus on a specific science use case, but rather on creating the body of knowledge and understanding that will inform future advances in extreme-scale science. Consequently, the funding from this FOA is not intended to incrementally extend current research in the area of the proposed project. It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches.

Exploratory Research for Extreme-Scale Science (EXPRESS) opportunities exist for the following research topics:

  • A. Harnessing Technology Innovations to Accelerate Science through Visualization
  • B. Scalable Space-Time Memories for Large Discrete/Agent-Based Models
  • C. Neuromorphic Computing
  • D. Advanced Wireless
  • E. Quantum Hardware Emulation

Applications submitted in response to this FOA must substantially address one among the preceding list of research topics.

Kalyan Perumalla
Kalyan Perumalla
R&D Manager

Kalyan Perumalla is an R&D Manager with 25 years of experience. As a Federal Program Manager in Advanced Scientific Computing Research at the U.S. Dept. of Energy, Office of Science, Kalyan Perumalla manages a $100-million R&D portfolio covering AI, HPC, Quantum, SciDAC, and Basic Computer Science. He previously led advanced R&D as Distinguished Research Staff Member at the Oak Ridge National Laboratory (ORNL) developing scalable software and applications on the world’s largest supercomputers for 17 years, including as a line manager and a founding group leader. He has held senior faculty and adjunct appointments at UTK, GT, and UNL, and was an IAS Fellow at Durham University.

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