11 citations · 14 across the 3 of their papers we have counts for
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cs.DC2019
AccD: A Compiler-based Framework for Accelerating Distance-related Algorithms on CPU-FPGA Platforms
Yuke Wang, Boyuan Feng, Gushu Li +3
As a promising solution to boost the performance of distance-related algorithms (e.g., K-means and KNN), FPGA-based acceleration attracts lots of attention, but also comes with num…
cs.DC2019
KPynq: A Work-Efficient Triangle-Inequality based K-means on FPGA
Yuke Wang, Zhaorui Zeng, Boyuan Feng +2
K-means is a popular but computation-intensive algorithm for unsupervised learning. To address this issue, we present KPynq, a work-efficient triangle-inequality based K-means on F…
cs.DC2018
Challenges Towards Deploying Data Intensive Scientific Applications on Extreme Heterogeneity Supercomputers
Hang Liu, Yufei Ding, Da Zheng +2
Shrinking transistors, which powered the advancement of computing in the past half century, has stalled due to power wall; now extreme heterogeneity is promised to be the next driv…