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cs.AR2026
Exposing Embedded Matrix Multiplication with polyhedral transformations for CGRA compilation
Yuxuan Wang, María José Belda, Fernando Castro +3
Matrix-matrix multiplication (mmul) is a dominant computing pattern in edge workloads, but in real applications it is often embedded within larger affine programs and intertwined w…
cs.AR2026
Mitigating the Bandwidth Wall via Data-Streaming System-Accelerator Co-Design
Qunyou Liu, Marina Zapater, David Atienza
Transformers have revolutionized AI in natural language processing and computer vision, but their large computation and memory demands pose major challenges for hardware accelerati…