STM-Multifrontal QR: Streaming Task Mapping Multifrontal QR Factorization Empowered by GCN

Multifrontal QR algorithm, which consists of symbolic analysis and numerical factorization, is a high-performance algorithm for orthogonal factorizing sparse matrix. In this work, a graph convolutional network (GCN) for adaptively selecting the optimal reordering algorithm is proposed in symbolic an...

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Vydáno v:	SC21: International Conference for High Performance Computing, Networking, Storage and Analysis s. 01 - 14
Hlavní autoři:	Lin, Shengle, Yang, Wangdong, Wang, Haotian, Tsai, Qinyun, Li, Kenli
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	ACM 14.11.2021
Témata:	Approximation algorithms Classification algorithms Computer architecture Graph Convolutional Network High performance computing Multicore processing Multifrontal QR Factorization NUMA Multicore Architecture Parallel processing Performance gain Task Mapping Optimization Task Stream Processing
ISSN:	2167-4337
On-line přístup:	Získat plný text
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