Workshop paper
Exploration of Unary Based GEMM Designs for Conventional AI/DL Accelerators
This paper surveys unary-based GEMM design points for more conventional AI accelerators. It explores how unary arithmetic may fit into mainstream inference hardware without requiring a full architectural reset.
Abstract Summary
This paper surveys unary-based GEMM design points for more conventional AI accelerators. It explores how unary arithmetic may fit into mainstream inference hardware without requiring a full architectural reset.
Research Context
This paper contributes to my research program in GEMM, unary computing, WUC 2024. It is part of the broader work on efficient ML systems, hardware-software co-design, and deployment-aware computer architecture.