9 citations · 9 across the 5 of their papers we have counts for
Showing 2026 · cs.ARShow all
2 papers · 2 filters
cs.AR2026
MEDEM: Multi-Engine DL Accelerator Design Methodology
Fareed Qararyah, Mohammad Ali Maleki, Pedro Trancoso
Multi-engine deep learning (DL) accelerators are becoming increasingly prevalent as they address the heterogeneity and growing complexity of modern DL workloads. To efficiently pro…
cs.AR2026
SISA: A Scale-In Systolic Array for GEMM Acceleration
Luigi Altamura, Alessio Cicero, Mateo Vázquez Maceiras +2
The currently dominant AI/ML workloads, such as Large Language Models (LLMs), rely on the efficient execution of General Matrix-Matrix Multiplication (GEMM) operations. Thus, most…