Parallel Search Algorithms
Parallel Search Algorithms is a class of parallel algorithms designed to systematically explore large solution spaces concurrently by leveraging multiple processing units, distinguished from other parallel algorithms by their focus on accelerating search operations through divide-and-conquer, pruning, or heuristic-guided exploration in scalable and fault-tolerant computational environments.
690
Publications
47.2K
Citations
1.6K
Authors
659
Institutions
Publications per year
2017–2026
119
690
DNA Solution of Hard Computational Problems
Richard J. Lipton · Science · 1995 · 1.1K citations
A Survey of Parallel Genetic Algorithms
Erick Cantú‐Paz · 2000 · 903 citations
Auto-Keras: An Efficient Neural Architecture Search System
Haifeng Jin, Qingquan Song, Xia Hu · 2019 · 855 citations · Full text
1–5 of 690
1.6K
8
h-index
8
h-index
7
h-index
7
h-index
6
h-index
1–5 of 1.6K
659

University of Minnesota
Minneapolis, United States
13 h-index
24 publications
993 citations

Centre National de la Recherche Scientifique
Paris, France
12 h-index
30 publications
1.8K citations
The University of Texas at Austin
Austin, United States
11 h-index
20 publications
1.3K citations

Universidad de Málaga
Málaga, Spain
10 h-index
19 publications
1.7K citations
The University of Tokyo
Tokyo, Japan
10 h-index
22 publications
558 citations

University of Alberta
Edmonton, Canada
9 h-index
19 publications
464 citations

Paderborn University
Paderborn, Germany
8 h-index
21 publications
890 citations
Virginia Tech
Blacksburg, United States
8 h-index
11 publications
613 citations
1–8 of 659
TPDS · 12 publications · 408 citations
12
h-index
14 publications · 496 citations
12
h-index
10 publications · 391 citations
10
h-index
Repository · 8 publications · 404 citations
8
h-index
7 publications · 256 citations
7
h-index
1–5