S-Caffe-Reference-Cited by-同舟云学术

S-Caffe

Published:2017-01-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
language:
Short-container-title:

Author:

Awan Ammar Ahmad¹,Hamidouche Khaled¹,Hashmi Jahanzeb Maqbool¹,Panda Dhabaleswar K.¹

Affiliation:

1. The Ohio State University, Columbus, OH, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3018743.3018769

Reference49 articles.

1. Caffe: Multi-GPU Usage and Performance. https://github.com/yahoo/caffe/blob/master/docs/multigpu.md. Caffe: Multi-GPU Usage and Performance. https://github.com/yahoo/caffe/blob/master/docs/multigpu.md.

2. KESCH : Cray CS-Storm System. http://www.cscs.ch/computers/kesch_escha/index.html. KESCH: Cray CS-Storm System. http://www.cscs.ch/computers/kesch_escha/index.html.

3. Intel Caffe. https://github.com/intelcaffe. Intel Caffe. https://github.com/intelcaffe.

4. A Unified Runtime System for Heterogeneous Multicore Architectures. http://starpu.gforge.inria.fr. A Unified Runtime System for Heterogeneous Multicore Architectures. http://starpu.gforge.inria.fr.

Cited by 37 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. gZCCL: Compression-Accelerated Collective Communication Framework for GPU Clusters;Proceedings of the 38th ACM International Conference on Supercomputing;2024-05-30

2. A Generic Performance Model for Deep Learning in a Distributed Environment;IEEE Access;2024

3. PiP-MColl: Process-in-Process-based Multi-object MPI Collectives;2023 IEEE International Conference on Cluster Computing (CLUSTER);2023-10-31

4. DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining;2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS);2023-07

5. ScaMP: Scalable Meta-Parallelism for Deep Learning Search;2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid);2023-05