Custom Compute for Edge AI: Accelerating innovation with Lund University and Codasip University Program
In recent years, the rapid advancement and adoption of Artificial Intelligence (AI) on the edge has brought about a surge in development. As AI models like ChatGPT become more prevalent and accurate, the computational requirements for inference also escalate. This necessitates architectural innovations aimed at reducing both power consumption and latency. The need for edge […]
A custom RISC-V vector instruction to accelerate structured-sparse matrix multiplications
A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a predefined pattern of zero values in the matrix, unlike unstructured sparsity where zeros can occur anywhere. The research was conducted by Democritus University of Thrace (DUTH) in Greece and was […]