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Keywords

  • QA75 Electronic computers. Computer science
  • high-performance computing

Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

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Research Output 1981 2020

FFT, FMM, and multigrid on the road to exascale: Performance challenges and opportunities

Ibeid, H., Olson, L. & Gropp, W., Feb 2020, In : Journal of Parallel and Distributed Computing. 136, p. 63-74 12 p.

Research output: Contribution to journalArticle

Multigrid Method
Fast Fourier transforms
Memory Hierarchy
Elliptic PDE
Heterogeneous Systems

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era

Allen, G., Andreoni, I., Bachelet, E., Berriman, G. B., Bianco, F. B., Biswas, R., Kind, M. C., Chard, K., Cho, M., Cowperthwaite, P. S., Etienne, Z. B., George, D., Gibbs, T., Graham, M., Gropp, W., Gupta, A., Haas, R., Huerta, E. A., Jennings, E., Katz, D. S. & 28 others, Khan, A., Kindratenko, V., Kramer, W. T. C., Liu, X., Mahabal, A., McHenry, K., Miller, J. M., Neubauer, M. S., Oberlin, S., Jr, A. R. O., Rosofsky, S., Ruiz, M., Saxton, A., Schutz, B., Schwing, A., Seidel, E., Shapiro, S. L., Shen, H., Shen, Y., Sipőcz, B. M., Sun, L., Towns, J., Tsokaros, A., Wei, W., Wells, J., Williams, T. J., Xiong, J. & Zhao, Z., Feb 1 2019, 15 p.

Research output: Book/ReportCommissioned report

Astrophysics
Artificial intelligence
Gravity waves
Astronomy
Big data

Enabling real-time multi-messenger astrophysics discoveries with deep learning

Huerta, E. A., Allen, G., Andreoni, I., Antelis, J. M., Bachelet, E., Berriman, G. B., Bianco, F. B., Biswas, R., Carrasco kind, M., Chard, K., Cho, M., Cowperthwaite, P. S., Etienne, Z. B., Fishbach, M., Forster, F., George, D., Gibbs, T., Graham, M., Gropp, W., Gruendl, R. & 40 others, Gupta, A., Haas, R., Habib, S., Jennings, E., Johnson, M. W. G., Katsavounidis, E., Katz, D. S., Khan, A., Kindratenko, V., Kramer, W. T. C., Liu, X., Mahabal, A., Marka, Z., Mchenry, K., Miller, J. M., Moreno, C., Neubauer, M. S., Oberlin, S., Olivas, A. R., Petravick, D., Rebei, A., Rosofsky, S., Ruiz, M., Saxton, A., Schutz, B. F., Schwing, A., Seidel, E., Shapiro, S. L., Shen, H., Shen, Y., Singer, L. P., Sipocz, B. M., Sun, L., Towns, J., Tsokaros, A., Wei, W., Wells, J., Williams, T. J., Xiong, J. & Zhao, Z., Oct 1 2019, In : Nature Reviews Physics. 1, 10, p. 600-608

Research output: Contribution to journalArticle

learning
astrophysics
recommendations
gravitational waves
machine learning

Exploring the feasibility of lossy compression for PDE simulations

Calhoun, J., Cappello, F., Olson, L. N., Snir, M. & Gropp, W. D., Mar 1 2019, In : International Journal of High Performance Computing Applications. 33, 2, p. 397-410 14 p.

Research output: Contribution to journalArticle

Lossy Compression
Checkpoint
Partial differential equations
Restart
Partial differential equation

Guest editor's introduction: Special issue on best papers from EuroMPI/USA 2017

Gropp, W. D. & Thakur, R., May 2019, In : Parallel Computing. 84, 1 p.

Research output: Contribution to journalEditorial

Honors & Recognition