.png){kind=icon}
Return
Lock-free parallel dynamic programming
.png){kind=icon}
OA
AI
DOI：10.1016/j.jpdc.2010.01.004.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We show a method for parallelizing top down dynamic programs in a straightforward way by a careful choice of a lock-free shared hash table implementation and randomization of the order in which the dynamic program computes its subproblems. This generic approach is applied to dynamic programs for knapsack, shortest paths, and RNA structure alignment, as well as to a state-of-the-art solution for minimizing the maximum number of open stacks. Experimental results are provided on three different modern multicore architectures which show that this parallelization is effective and reasonably scalable. In particular, we obtain over 10 times speedup for 32 threads on the open stacks problem. (C) 2010 Elsevier Inc. All rights reserved.
Keywords:
Dynamic programming
Lock-free hash tables
Constraint programming
Multicores
Parallelism
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4
Papers:
3.8K
Citations:
4.8K
Organization
Cited Papers
ShareSaveCharacterization of polymer matrix and low melting point solder for anisotropic conductive film
PREAI
ShareSaveShareSaveA benchmark of multiple sequence alignment programs upon structural RNAs.png)
NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAIShareSave
View more