Full Program

Despite tremendous improvement in absolute capacity and speed, the storage subsystem remains one of the slower, less predictable, and less scalable components of large-scale applications. In this talk, through a personal journey of parallel and distributed storage systems, I hope to share observations and lessons from these past projects. In particular, across the many layers of the storage hierarchy studied, from the CPU caches to supercomputer and cloud storage clusters, we repeatedly encounter the same underlying challenge of efficient sharing of I/O resources. Without effective regulation of I/O flows, the storage system can easily be a performance bottleneck while remaining largely underutilized. The discussion of solutions continues into related new (and old) storage problems with today's parallel AI training and inference workloads.

Professor Ma’s main research focus has been on efficient resource utilization across different system layers, from CPU/GPU caches to datacenter-scale distributed storage. Her research projects share the common theme of reducing or eliminating waste in systems software, to better support applications including graph, database, and LLM processing.