Memory Transfer Decomposition: Exploring Smart Data Movement Through Architecture-Aware Strategies-Reference-Cited by-同舟云学术

Memory Transfer Decomposition: Exploring Smart Data Movement Through Architecture-Aware Strategies

Published:2023-11-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
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Author:

Roa Perdomo Diego A.¹^ORCID,Ceccato Rodrigo²^ORCID,Neveu Rémy²^ORCID,Yviquel Hervé³^ORCID,Li Xiaoming⁴^ORCID,Monsalve Diaz Jose M.⁵^ORCID,Doerfert Johannes⁶^ORCID

Affiliation:

1. Electrical and Computer Engineering, University of Delaware - CAPSL, United States of America and Argonne National Laboratory (ANL), United States of America

2. University of Campinas, Brazil and Argonne National Laboratory, USA

3. University of Campinas, Brazil

4. University of Delaware, United States of America

5. Argonne National Laboratory, United States of America

6. Lawrence Livermore National Laboratory, United States of America

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3624062.3624609

Reference37 articles.

1. Patrick Atkinson and Simon McIntosh-Smith . 2017. On the Performance of Parallel Tasking Runtimes for an Irregular Fast Multipole Method Application . In Scaling OpenMP for Exascale Performance and Portability, Bronis R. de Supinski, Stephen L . Olivier, Christian Terboven, Barbara M. Chapman, and Matthias S. Müller (Eds.). Springer International Publishing , Cham , 92–106. Patrick Atkinson and Simon McIntosh-Smith. 2017. On the Performance of Parallel Tasking Runtimes for an Irregular Fast Multipole Method Application. In Scaling OpenMP for Exascale Performance and Portability, Bronis R. de Supinski, Stephen L. Olivier, Christian Terboven, Barbara M. Chapman, and Matthias S. Müller (Eds.). Springer International Publishing, Cham, 92–106.

2. StarPU: a unified platform for task scheduling on heterogeneous multicore architectures

3. Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters

4. Alan Ayala , Stanimire Tomov , Miroslav Stoyanov , and Jack Dongarra . 2021. Scalability Issues in FFT Computation . In Parallel Computing Technologies, Victor Malyshkin (Ed.). Springer International Publishing , Cham , 279–287. Alan Ayala, Stanimire Tomov, Miroslav Stoyanov, and Jack Dongarra. 2021. Scalability Issues in FFT Computation. In Parallel Computing Technologies, Victor Malyshkin (Ed.). Springer International Publishing, Cham, 279–287.

5. UPC++: A High-Performance Communication Framework for Asynchronous Computation