Luke Everson

About

Luke Everson is a leading researcher in energy-efficient computing architectures, with a focus on in-memory computing and graph processing hardware. His most impactful work centers on developing novel application-specific integrated circuits (ASICs) that accelerate graph algorithms, particularly single-source shortest path (SSP) problems, which are critical for applications ranging from AI decision-making and robot navigation to autonomous vehicles and VLSI signal routing. Everson’s landmark paper, "A 40×40 Four-Neighbor Time-Based In-Memory Computing Graph ASIC Chip Featuring Wavefront Expansion and 2D Gradient Control" (2019), has garnered 11 citations and demonstrates a pioneering approach to solving SSP problems directly in hardware. By leveraging time-based in-memory computing and wavefront expansion techniques, his chip achieves significant performance and energy efficiency gains over conventional algorithmic implementations. This work represents a major contribution to the field of graph processing hardware, offering a scalable and practical solution for real-time, low-power graph traversal in embedded and edge computing environments. Everson’s research bridges the gap between theoretical graph algorithms and practical, high-performance hardware, making him a key figure in the advancement of next-generation computing systems.

Research Focus

Key Achievements

Top Papers

1. 1
   2.5 A 40×40 Four-Neighbor Time-Based In-Memory Computing Graph ASIC Chip Featuring Wavefront Expansion and 2D Gradient Control

   11 citations · 2019

Key Collaborators

Contact & Links