High-throughput Computing
High-Throughput Computing is a computational paradigm within distributed computing that emphasizes the efficient execution of a large number of computational tasks over extended periods, distinguished from high-performance computing by its focus on maximizing aggregate task throughput rather than minimizing the execution time of individual tasks.
862
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45.9K
Citations
3.4K
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718
Institutions
Publications per year
2017–2026
310
862
Sorting networks and their applications
Kenneth E. Batcher · 1968 · 2.4K citations
Yu‐Hsin Chen, Joel Emer, Vivienne Sze · ACM SIGARCH Computer Architecture News · 2016 · 1.2K citations
GPUs and the Future of Parallel Computing
Stephen W. Keckler, William J. Dally, Brucek Khailany et al. · IEEE Micro · 2011 · 664 citations
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Argonne National Laboratory
Lemont, United States
22 h-index
98 publications
5.7K citations
Intel (United States)
Santa Clara, United States
22 h-index
150 publications
22.5K citations
University of Wisconsin–Madison
Madison, United States
19 h-index
54 publications
4.6K citations

Lawrence Berkeley National Laboratory
Berkeley, United States
18 h-index
86 publications
8.2K citations
University of Illinois Urbana-Champaign
Urbana, United States
18 h-index
66 publications
3K citations
ETH Zurich
Zurich, Switzerland
17 h-index
50 publications
3.6K citations
University of California, Berkeley
Berkeley, United States
16 h-index
77 publications
4.7K citations
University of Southern California
Los Angeles, United States
16 h-index
69 publications
2.6K citations
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Repository · 27 publications · 859 citations
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PVLDB · 18 publications · 1.5K citations
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TPDS · 18 publications · 670 citations
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13 publications · 1K citations
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10 publications · 520 citations
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