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Performance and Algorithms Research

SciDAC-5 Institute

Researchers from PAR are engaged in a number of activities in the Scientific Discovery through Advanced Computing (SciDAC) initiative. The SciDAC program was initiated in 2001 in order to develop the Scientific Computing Software and Hardware Infrastructure needed to advance scientific discovery using supercomputers. As supercomputers continuously evolve, direct engagement of computer scientists and applied mathematicians with the scientists of targeted application domains becomes ever more necessary for taking full advantage of these new systems. In this regard, SciDAC is a partnership involving all of the Department of Energy (DOE) Office of Science (SC) programs - Advanced Scientific Computing Research (ASCR), Basic Energy Sciences (BES), Biological and Environmental Research (BER), Fusion Energy Sciences (FES), High-Energy Physics (HEP) and Nuclear Physics (NP) - to dramatically accelerate progress in scientific computing that delivers breakthrough scientific results through partnerships comprised of applied mathematicians, computer scientists, and scientists from other disciplines.

Researchers within PAR engage in computer science research covering Performance Modeling, Machine Learning, Communication Runtimes as well as performance optimization of various SciDAC applications. 

Researchers

Projects

  • RAPIDS SciDAC Institute for CS & Data
    • Roofline, a visually-intuitive performance model for multicore, manycore, and accelerated systems
  • SciDAC Application Partnerships
    • Real-time Dynamics of Driven Correlated Electrons in Quantum Materials
    • DECODE: Data-driven Exascale Control of Optically Driven Excitations in Chemical
    • EFIT-AI: Creating a performance-portable tool for Tokamak plasma reconstruction

Publications

Conference Paper

2024

Oscar Antepara, Samuel Williams, Max Carlson, Jerry Watkins, "Performance Portable Optimizations of an Ice-sheet Modeling Code on GPU-supercomputers", Performance, Portability & Productivity in HPC (P3HPC), November 2024,

Sterling Smith, Zichuan Anthony Xing, Torrin Bechtel, Severin Denk, Earl DeShazer, Orso Meneghini, Tom Neiser, Laurie Stephey, Oscar Antepara, Christopher Mitchell Clark, Eli Dart, Pengfei Ding, Sean Flanagan, Raffi Nazikian, David Schissel, Christine Simpson, Nicholas Tyler, Thomas D. Uram, Samuel Williams, "Expediting Higher Fidelity Plasma State Reconstructions for the DIII-D National Fusion Facility Using Leadership Class Computing Resources", Extreme-Scale Experiment-in-the-Loop Computing (XLOOP), November 2024,

2023

Yang Liu, Nan Ding, Piyush Sao, Samuel Williams, Xiaoye Sherry Li, "Unified Communication Optimization Strategies for Sparse Triangular Solver on CPU and GPU Clusters", Supercomputing (SC), November 2023,

Presentation/Talk

2023

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, February 8, 2023,

2022

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, May 2022,

Neil Mehta, Roofline on NVIDIA at NERSC, ECP Annual Meeting, May 2022,

JaeHyuk Kwack, ROOFLINE PERFORMANCE ANALYSIS W/ INTEL ADVISOR ON INTEL CPUS & GPUS, ECP Annual Meeting, May 2022,