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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. 







Charlene Yang, Rahulkumar Gayatri, Thorsten Kurth, Protonu Basu, Zahra Ronaghi, Adedoyin Adetokunbo, Brian Friesen, Brandon Cook, Douglas Doerfler, Leonid Oliker, Jack Deslippe, Samuel Williams, "An Empirical Roofline Methodology for Quantitatively Assessing Performance Portability", International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November 2018,

Hongzhang Shan, Samuel Williams, Calvin W. Johnson, "Improving MPI Reduction Performance for Manycore Architectures with OpenMP and Data Compression", Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November 2018,

Samuel Williams, Introduction to the Roofline Model, Supercomputing, November 2018,

Samuel Williams, Roofline on Manycore and Accelerated Systems, ModSim, August 2018,

Samuel Williams, Parallelism and Performance, MolSSI Summer School, August 2018,

Khaled Ibrahim, Samuel Williams, Leonid Oliker, "Roofline Scaling Trajectories: A Method for Parallel Application and Architectural Performance Analysis", HPCS Special Session on High Performance Computing Benchmarking and Optimization (HPBench), July 2018,

Tuomas Koskela, Zakhar Matveev, Charlene Yang, Adetokunbo Adedoyin4, Roman Belenov, Philippe Thierry, Zhengji Zhao, Rahulkumar Gayatri, Hongzhang Shan, Leonid Oliker, Jack Deslippe, Ron Green, and Samuel Williams, "A Novel Multi-Level Integrated Roofline Model Approach for Performance Characterization", ISC, June 2018,

Charlene Yang, Brian Friesen, Thorsten Kurth, Brandon Cook, Samuel Williams, "Toward Automated Application Profiling on Cray Systems", Cray User Group (CUG), May 2018,

Protonu Basu, Using Empirical Roofline Toolkit and Nvidia nvprof, ECP Annual Meeting, February 8, 2018,

Samuel Williams, Introduction to the Roofline Model, ECP Annual Meeting, February 8, 2018,

Jack Deslippe, Guiding Optimization on KNL with the Roofline Model, ECP Annual Meeting, February 8, 2018,

Charlene Yang, LIKWID at NERSC, ECP Annual Meeting, February 8, 2018,

Charlene Yang, Intel Advisor on Cori, ECP Annual Meeting, February 8, 2018,

Samuel Williams, Advisor Hand-On: Stencil Example, ECP Annual Meeting, February 8, 2018,

Samuel Williams, Performance Modeling and Analysis, CS267 lecture, University of California at Berkeley, January 30, 2018,