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RSDHA@SC 2021: St. Louis, MO, USA

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IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop, RSDHA@SC 2021, St. Louis, MO, USA, November 19, 2021. IEEE 2021, ISBN 978-1-6654-5877-1
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Ismet Dagli, Mehmet E. Belviranli:
Multi-accelerator Neural Network Inference in Diversely Heterogeneous Embedded Systems. 1-7
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  - conf/sc/MonilLVM21
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Mohammad Alaul Haque Monil, Seyong Lee, Jeffrey S. Vetter, Allen D. Malony:
Comparing LLC-Memory Traffic between CPU and GPU Architectures. 8-16
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Clayton J. Faber, Tom Plano, Samatha Kodali, Zhili Xiao, Abhishek Dwaraki, Jeremy D. Buhler, Roger D. Chamberlain, Anthony M. Cabrera:
Platform Agnostic Streaming Data Application Performance Models. 17-26
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  - conf/sc/TsarisHLD21
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Aristeidis Tsaris, Jacob D. Hinkle, Dalton D. Lunga, Philipe Ambrozio Dias:
Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach. 27-33
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Jordan Schmerge, Daniel Mawhirter, Connor Holmes, Jedidiah McClurg, Bo Wu:
ELIχR: Eliminating Computation Redundancy in CNN-Based Video Processing. 34-44
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Marcus Chow, Kiran Ranganath, Robert Lerias, Mika Shanela Carodan, Daniel Wong:
Energy Efficient Task Graph Execution Using Compute Unit Masking in GPUs. 45-51

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