Leul Wuletaw Belayneh

I am a Ph.D. candidate in Computer Science and Engineering at the University of Michigan where I am advised by Prof. Ron Dreslinski. Priorly, I received my bachelor’s degree from Addis Ababa Institute of Technology.

Research

My research spans the area of computer architecture, particularly focusing on accelerating data-intensive applications. I design hardware and software optimizations to improve the performance and energy efficiency of data-intensive workloads on conventional and emerging architectures like Processing-in-Memory (PIM). One of the challenges in the era of big data, is the increasing gap between compute performance and memory bandwidth, which has been partially addressed by in/near memory computing architectures. However, harnessing the high memory bandwidth in these architectures is hampered by the interconnect, which incurs costly data movement. To address this, my thesis proposes custom hardware (memory subsystem including interconnect) and software optimizations to improve the performance and energy efficiency of massively parallel processors.

In my recent work [PACT'22], I have proposed fine-grained inter-GPU data movement and novel caching techniques to improve the performance and scalability of multi-GPU workloads. I have also explored ways to reduce excess data movement in PIM-based graph execution through a processing-in-network solution [ISLPED'19] and multicasting techniques [DATE'20].