Search Results for author: Mateo Valero

Found 2 papers, 1 papers with code

The Ultimate DataFlow for Ultimate SuperComputers-on-a-Chip, for Scientific Computing, Geo Physics, Complex Mathematics, and Information Processing

no code implementations20 Sep 2020 Veljko Milutinovic, Erfan Sadeqi Azer, Kristy Yoshimoto, Gerhard Klimeck, Miljan Djordjevic, Milos Kotlar, Miroslav Bojovic, Bozidar Miladinovic, Nenad Korolija, Stevan Stankovic, Nenad Filipović, Zoran Babovic, Miroslav Kosanic, Akira Tsuda, Mateo Valero, Massimo De Santo, Erich Neuhold, Jelena Skoručak, Laura Dipietro, Ivan Ratkovic

This article starts from the assumption that near future 100BTransistor SuperComputers-on-a-Chip will include N big multi-core processors, 1000N small many-core processors, a TPU-like fixed-structure systolic array accelerator for the most frequently used Machine Learning algorithms needed in bandwidth-bound applications and a flexible-structure reprogrammable accelerator for less frequently used Machine Learning algorithms needed in latency-critical applications.

Distributed, Parallel, and Cluster Computing

Improving accuracy and speeding up Document Image Classification through parallel systems

1 code implementation16 Jun 2020 Javier Ferrando, Juan Luis Dominguez, Jordi Torres, Raul Garcia, David Garcia, Daniel Garrido, Jordi Cortada, Mateo Valero

This paper presents a study showing the benefits of the EfficientNet models compared with heavier Convolutional Neural Networks (CNNs) in the Document Classification task, essential problem in the digitalization process of institutions.

Document Classification Document Image Classification +4

Cannot find the paper you are looking for? You can Submit a new open access paper.