Spiral/AIML: Resource-Constrained Co-Optimization for High-Performance, Data-Intensive Computing
November 2019 • Video
Watch SEI Principal Investigator, Dr. Scott McMillan, and research collaborator, CMU ECE Professor Franz Franchetti, discuss a community research effort to develop tools to reduce the prohibitive cost of implementing and re-implementing AI/ML software on
Software Engineering Institute
As the military adopts AI/ML to augment human teams, the cost of implementing and re-implementing AI/ML software on new hardware platforms will be prohibitive. To address these challenges, we propose to develop a hardware-software co-optimization system that will (1) automatically search and select hardware configurations optimized for a specified computation and (2) autonomously generate optimized codes for the selected hardware configuration and the irregular, data-intensive computations required for AI/ML algorithms.