24 citations · 71 across the 6 of their papers we have counts for
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cs.LG2023★ 24 cited
Taming Resource Heterogeneity In Distributed ML Training With Dynamic Batching
Sahil Tyagi, Prateek Sharma
Current techniques and systems for distributed model training mostly assume that clusters are comprised of homogeneous servers with a constant resource availability. However, clust…
cs.DC2023★ 6 cited
Scavenger: A Cloud Service for Optimizing Cost and Performance of ML Training
Sahil Tyagi, Prateek Sharma
While the pay-as-you-go nature of cloud virtual machines (VMs) makes it easy to spin-up large clusters for training ML models, it can also lead to ballooning costs. The 100s of vir…