2022-05-17 - Nan Ding - Memory Disaggregation: Potentials and Pitfalls
Channel: NERSC
Date: 2022-05-17

NERSC Data Seminars Series: https://github.com/NERSC/data-seminars

Title:
Memory Disaggregation: Potentials and Pitfalls

Speaker:
Nan Ding, Performance and Algorithms Group, Computer Science Department, Lawrence Berkeley National Laboratory

Abstract:
Memory usage imbalance has been consistently observed in many data centers. This has sparked interest in memory disaggregation, which allows applications to use all available memory across an entire data center instead of being confined to the memory of a single server. In the talk, I'll present the design space and implementation for building a disaggregated memory system. I'll then discuss the critical metrics for applications to benefit from memory disaggregation.

Bio:
Nan Ding is a Research Scientist in the Performance and Algorithms group of the Computer Science Department at Lawrence Berkeley National Laboratory. Her research interests include high-performance computing, performance modeling, and auto-tuning. Nan received her Ph.D. in computer science from Tsinghua University, Beijing, China in 2018.

Host of Seminar:
Hai Ah Nam, Advanced Technologies Group
National Energy Research Scientific Computing Center (NERSC)
Lawrence Berkeley National Laboratory