1.9k citations · 2.5k across the 16 of their papers we have counts for
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cs.DC2022
DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads
Seah Kim, Hyoukjun Kwon, Jinook Song +4
Emerging real-time multi-model ML (RTMM) workloads such as AR/VR and drone control involve dynamic behaviors in various granularity; task, model, and layers within a model. Such dy…
cs.LG2022★ 12 cited
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse
Hyoukjun Kwon, Krishnakumar Nair, Jamin Seo +15
Real-time multi-task multi-model (MTMM) workloads, a new form of deep learning inference workloads, are emerging for applications areas like extended reality (XR) to support metave…