CuMAS
Author:
Affiliation:
1. Computer Science Department, University of California, Riverside
Funder
NSF
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2925426.2926271
Reference28 articles.
1. The case for GPGPU spatial multitasking
2. An adaptive performance modeling tool for GPU architectures
3. A virtual memory based runtime to support multi-tenancy in clusters with GPUs
Cited by 7 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. An Analysis of Collocation on GPUs for Deep Learning Training;Proceedings of the 4th Workshop on Machine Learning and Systems;2024-04-22
2. Shared Memory-contention-aware Concurrent DNN Execution for Diversely Heterogeneous System-on-Chips;Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming;2024-02-20
3. Characterizing concurrency mechanisms for NVIDIA GPUs under deep learning workloads;Performance Evaluation;2021-11
4. FusionCL: a machine-learning based approach for OpenCL kernel fusion to increase system performance;Computing;2021-06-03
5. MEPHESTO;Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques;2020-09-30
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