180 citations · 520 across the 35 of their papers we have counts for
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cs.DC2020
LazyBatching: An SLA-aware Batching System for Cloud Machine Learning Inference
Yujeong Choi, Yunseong Kim, Minsoo Rhu
In cloud ML inference systems, batching is an essential technique to increase throughput which helps optimize total-cost-of-ownership. Prior graph batching combines the individual…
cs.AR2020
Tensor Casting: Co-Designing Algorithm-Architecture for Personalized Recommendation Training
Youngeun Kwon, Yunjae Lee, Minsoo Rhu
Personalized recommendations are one of the most widely deployed machine learning (ML) workload serviced from cloud datacenters. As such, architectural solutions for high-performan…
cs.DC2020★ 6 cited
Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations
Ranggi Hwang, Taehun Kim, Youngeun Kwon +1
Personalized recommendations are the backbone machine learning (ML) algorithm that powers several important application domains (e.g., ads, e-commerce, etc) serviced from cloud dat…