Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Francesco Sgherzi"'
Publikováno v:
FCCM
Large-scale eigenvalue computations on sparse matrices are a key component of graph analytics techniques based on spectral methods. In such applications, an exhaustive computation of all eigenvalues and eigenvectors is impractical and unnecessary, as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45ca6b35e5858318a2b90fa26122a02d
http://arxiv.org/abs/2103.10040
http://arxiv.org/abs/2103.10040
Publikováno v:
ASP-DAC
Sparse matrix-vector multiplication is often employed in many data-analytic workloads in which low latency and high throughput are more valuable than exact numerical convergence. FPGAs provide quick execution times while offering precise control over
Autor:
Li, Yueting, Wang, Xueyan, Zhang, He, Pan, Biao, Qiu, Keni, Kang, Wang, Wang, Jun, Zhao, Weisheng
Publikováno v:
ACM Transactions on Embedded Computing Systems; May2024, Vol. 23 Issue 3, p1-24, 24p
Publikováno v:
ACM Computing Surveys; Jan2024, Vol. 56 Issue 1, p1-38, 38p, 1 Illustration
This book constitutes the proceedings of the 37th International Conference on Architecture of Computing Systems, ARCS 2024, held in Potsdam, Germany, in May 2024. The 23 papers presented in this volume were carefully reviewed and selected from 33