Categories – User Experiments

Zeus: GPU Energy as a First-Class Resource in DNN Training

In this month's user experiment blog we get a fascinating insight into how much power training deep neural networks (DNNs) consumes – and how to make it less. The authors’ discuss research presented as part of their NSDI ’23 paper, describe how they structured their experiments on Chameleon, and explain why bare metal resources are essential for power management research. 

Exploring Process-in-memory Architecture for High-performance Graph Pattern Mining

Graph Pattern Mining (GPMI) applications are considered a new class of data-intensive applications -- they generate massive irregular computation workloads and pose memory access challenges, which degrade the performance and scalability significantly. Researchers at the Illinois Institute of Technology approach the problem by using the emerging process-in-memory architecture.