3 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
TreeGRNG: Binary Tree Gaussian Random Number Generator for Efficient Probabilistic AI Hardware
Jonas Crols, Guilherme Paim, Shirui Zhao +1
Bayesian Neural Networks (BNNs) offer opportunities for greatly enhancing the trustworthiness of conventional neural networks by monitoring the uncertainties in decision-making. A…
An Open-Source HW-SW Co-Development Framework Enabling Efficient Multi-Accelerator Systems
Ryan Albert Antonio, Joren Dumoulin, Xiaoling Yi +4
Heterogeneous accelerator-centric compute clusters are emerging as efficient solutions for diverse AI workloads. However, current integration strategies often compromise data movem…
DataMaestro: A Versatile and Efficient Data Streaming Engine Bringing Decoupled Memory Access To Dataflow Accelerators
Xiaoling Yi, Yunhao Deng, Ryan Antonio +3
Deep Neural Networks (DNNs) have achieved remarkable success across various intelligent tasks but encounter performance and energy challenges in inference execution due to data mov…
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…