29 citations · 63 across the 7 of their papers we have counts for
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cs.DC2020★ 18 cited
Efficient Execution of Quantized Deep Learning Models: A Compiler Approach
Animesh Jain, Shoubhik Bhattacharya, Masahiro Masuda +2
A growing number of applications implement predictive functions using deep learning models, which require heavy use of compute and memory. One popular technique for increasing reso…
cs.PF2020★ 6 cited
Optimizing Memory-Access Patterns for Deep Learning Accelerators
Hongbin Zheng, Sejong Oh, Huiqing Wang +7
Deep learning (DL) workloads are moving towards accelerators for faster processing and lower cost. Modern DL accelerators are good at handling the large-scale multiply-accumulate o…