Opportunistic computing in GPU architectures-Reference-Cited by-同舟云学术

Opportunistic computing in GPU architectures

Published:2019-06-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 46th International Symposium on Computer Architecture
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Author:

Pattnaik Ashutosh¹,Tang Xulong¹,Kayiran Onur²,Jog Adwait³,Mishra Asit⁴,Kandemir Mahmut T.¹,Sivasubramaniam Anand¹,Das Chita R.¹

Affiliation:

1. The Pennsylvania State University

2. Advanced Micro Devices, Inc.

3. College of William & Mary

4. NVIDIA Corp.

Funder

Defense Advanced Research Projects Agency

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3307650.3322212

Reference70 articles.

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2. Junwhan Ahn et al. 2015. PIM-enabled Instructions: A Low-overhead Locality-aware Processing-in-memory Architecture. In ISCA. Junwhan Ahn et al. 2015. PIM-enabled Instructions: A Low-overhead Locality-aware Processing-in-memory Architecture. In ISCA.

3. Ashwin Mandayam Aji et al. 2015. Automatic Command Queue Scheduling for Task-Parallel Workloads in OpenCL. In CLUSTER. Ashwin Mandayam Aji et al. 2015. Automatic Command Queue Scheduling for Task-Parallel Workloads in OpenCL. In CLUSTER.

4. MultiCL: Enabling automatic scheduling for task-parallel workloads in OpenCL

5. Jayvant Anantpur and R. Govindarajan. 2017. Taming Warp Divergence. In CGO. Jayvant Anantpur and R. Govindarajan. 2017. Taming Warp Divergence. In CGO.

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