activity
20172024
most citedE-PUR: An Energy-Efficient Processing Unit for Recurrent Neural Networks

36 citations · 52 across the 13 of their papers we have counts for

collaborators

14 papers

cs.DC2024

Vitamin-V: Expanding Open-Source RISC-V Cloud Environments

Ramon Canal, Stefano Di Carlo, Dimitris Gizopoulos +12

Among the key contributions of Vitamin-V (2023-2025 Horizon Europe project), we develop a complete RISC-V open-source software stack for cloud services with comparable performance…

cs.AR2023

A Lightweight, Compiler-Assisted Register File Cache for GPGPU

Mojtaba Abaie Shoushtary, Jose Maria Arnau, Jordi Tubella Murgadas +1

Modern GPUs require an enormous register file (RF) to store the context of thousands of active threads. It consumes considerable energy and contains multiple large banks to provide…

cs.DC2023

Vitamin-V: Virtual Environment and Tool-boxing for Trustworthy Development of RISC-V based Cloud Services

A. Arelakis, J. M. Arnau, J. L. Berral +20

Vitamin-V is a 2023-2025 Horizon Europe project that aims to develop a complete RISC-V open-source software stack for cloud services with comparable performance to the cloud-domina…

cs.AR2023★ 13 cited

K-D Bonsai: ISA-Extensions to Compress K-D Trees for Autonomous Driving Tasks

Pedro H. E. Becker, José María Arnau, Antonio González

Autonomous Driving (AD) systems extensively manipulate 3D point clouds for object detection and vehicle localization. Thereby, efficient processing of 3D point clouds is crucial in…

cs.AR2022

Exploiting Kernel Compression on BNNs

Franyell Silfa, Jose Maria Arnau, Antonio González

Binary Neural Networks (BNNs) are showing tremendous success on realistic image classification tasks. Notably, their accuracy is similar to the state-of-the-art accuracy obtained b…

cs.NE2022★ 1 cited

Saving RNN Computations with a Neuron-Level Fuzzy Memoization Scheme

Franyell Silfa, Jose-Maria Arnau, Antonio González

Recurrent Neural Networks (RNNs) are a key technology for applications such as automatic speech recognition or machine translation. Unlike conventional feed-forward DNNs, RNNs reme…