ML Training Acceleration with Heterogeneous Resources in ByteDance

ML Training Acceleration with Heterogeneous Resources in ByteDance

Explore machine learning training acceleration techniques using heterogeneous resources at ByteDance in this 19-minute conference talk from KubeCon + CloudNativeCon Europe 2022. Delve into strategies for maximizing GPU utilization through sharing mechanisms, optimizing resource allocation with NUMA affinity, and implementing high-throughput network communication using RDMA CNI and Intel SRIOV technology. Gain insights into empowering model training, enhancing performance for large-scale distributed models, and effectively managing diverse CPU/GPU resources. Cover topics including GPU offline training for network and scheduling, GPU online serving, unified GPU scheduling, and future developments in the field.