Parallelism Granularity
Parallelism Granularity is a measure in parallel computing that classifies the scale of computational tasks relative to communication and synchronization overhead, distinguishing itself by quantifying the size of atomic work units executed concurrently within a parallel system.
78
Publications
4.1K
Citations
236
Authors
113
Institutions
Publications per year
2017–2026
7
Parents
78
PipeLayer: A Pipelined ReRAM-Based Accelerator for Deep Learning
Linghao Song, Xuehai Qian, Hai Li et al. · 2017 · 821 citations
1–5 of 78
236
4
h-index
3
h-index
3
h-index
3
h-index
2
h-index
1–5 of 236
113
Stanford University
Stanford, United States
7 h-index
14 publications
874 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
11 publications
482 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
8 publications
152 citations
Yale University
New Haven, United States
3 h-index
3 publications
637 citations
University of Arizona
Tucson, United States
3 h-index
5 publications
345 citations
University of Chicago
Chicago, United States
3 h-index
8 publications
388 citations

University of St Andrews
St Andrews, United Kingdom
3 h-index
4 publications
67 citations
Toyota Technological Institute at Chicago
Chicago, United States
3 h-index
3 publications
127 citations
1–8 of 113
TPDS · 4 publications · 434 citations
4
h-index
2 publications · 113 citations
2
h-index
2 publications · 68 citations
2
h-index
2 publications · 24 citations
2
h-index
1 publications · 81 citations
1
h-index
1–5