Petuum Awarded OSDI 2021 Best Paper for Goodput-Optimized Deep Learning Research

Petuum's CASL research and engineering team has won this year's OSDI 2021 Best Paper Award. This effort is led by Dr. Aurick Qiao who heads the Composability, Automatic, and Scalable Learning (CASL) research and engineering team at Petuum. Dr. Qiao received the Jay Lepreau Best Paper Award at the 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI) 2021 for the paper he co-authored, Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning which captures the revolutionary work implemented using one of CASL's key components, AdaptDL. Current live application of Pollux can be implemented via AdaptDL that integrates with PyTorch, Microsoft NNI, and with Ray coming soon. Pollux as implemented by AdaptDL improves scheduling performance in deep learning (DL) clusters by adaptively co-optimizing inter-dependent factors both at the per-job level and at the cluster-wide level.