activity
20162020
most citedAnalyzing GPU Tensor Core Potential for Fast Reductions

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.DC2020

Efficient GPU Thread Mapping on Embedded 2D Fractals

Cristóbal A. Navarro, Felipe A. Quezada, Nancy Hitschfeld +2

This work proposes a new approach for mapping GPU threads onto a family of discrete embedded 2D fractals. A block-space map $λ: \mathbb{Z}_{\mathbb{E}}^{2} \mapsto \mathbb{Z}_{\mat…

cs.DC2020

GPU Tensor Cores for fast Arithmetic Reductions

Cristóbal A. Navarro, Roberto Carrasco, Ricardo J. Barrientos +2

This work proposes a GPU tensor core approach that encodes the arithmetic reduction of numbers as a set of chained matrix multiply accumulate (MMA) operations exec…

cs.DC20191 cited

Analyzing GPU Tensor Core Potential for Fast Reductions

Roberto Carrasco, Raimundo Vega, Cristóbal A. Navarro

The Nvidia GPU architecture has introduced new computing elements such as the \textit{tensor cores}, which are special processing units dedicated to perform fast matrix-multiply-ac…

cs.DC2017

Block-space GPU Mapping for Embedded Sierpiński Gasket Fractals

Cristóbal A. Navarro, Benjamín Bustos, Raimundo Vega +1

This work studies the problem of GPU thread mapping for a Sierpiński gasket fractal embedded in a discrete Euclidean space of . A block-space map $λ: \mathbb{Z}_{\mathb…

cs.DC2016

Potential benefits of a block-space GPU approach for discrete tetrahedral domains

Cristóbal A. Navarro, Benjamín Bustos, Nancy Hitschfeld

The study of data-parallel domain re-organization and thread-mapping techniques are relevant topics as they can increase the efficiency of GPU computations when working on spatial…