32 citations · 39 across the 3 of their papers we have counts for
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cs.AR2024★ 1 cited
OpenGeMM: A High-Utilization GeMM Accelerator Generator with Lightweight RISC-V Control and Tight Memory Coupling
Xiaoling Yi, Ryan Antonio, Joren Dumoulin +4
Deep neural networks (DNNs) face significant challenges when deployed on resource-constrained extreme edge devices due to their computational and data-intensive nature. While stand…
cs.AR2023★ 6 cited
Benchmarking and modeling of analog and digital SRAM in-memory computing architectures
Pouya Houshmand, Jiacong Sun, Marian Verhelst
In-memory-computing is emerging as an efficient hardware paradigm for deep neural network accelerators at the edge, enabling to break the memory wall and exploit massive computatio…