Enrique S. Quintana-Ortí | DeepAI

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∙ 04/27/2023

Co-Design of the Dense Linear AlgebravSoftware Stack for Multicore Processors

This paper advocates for an intertwined design of the dense linear algeb...

0 Héctor Martínez, et al. ∙

∙ 02/15/2023

Toward matrix multiplication for deep learning inference on the Xilinx Versal

The remarkable positive impact of Deep Neural Networks on many Artificia...

0 Jie Lei, et al. ∙

∙ 04/20/2022

Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence

The evolution of High-Performance Computing (HPC) platforms enables the ...

0 Jorge Ejarque, et al. ∙

∙ 05/19/2021

High performance and energy efficient inference for deep learning on ARM processors

We evolve PyDTNN, a framework for distributed parallel training of Deep ...

0 Adrián Castelló, et al. ∙

∙ 10/26/2020

Resiliency in Numerical Algorithm Design for Extreme Scale Simulations

This work is based on the seminar titled “Resiliency in Numerical Algori...

0 Emmanuel Agullo, et al. ∙

∙ 09/25/2020

Compressed Basis GMRES on High Performance GPUs

Krylov methods provide a fast and highly parallel numerical tool for the...

0 José I. Aliaga, et al. ∙

∙ 06/30/2020

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

In this paper, we present Ginkgo, a modern C++ math library for scientif...

0 Hartwig Anzt, et al. ∙

∙ 05/14/2020

Reproducibility of Parallel Preconditioned Conjugate Gradient in Hybrid Programming Environments

The Preconditioned Conjugate Gradient method is often employed for the s...

0 Roman Iakymchuk, et al. ∙

∙ 05/13/2020

High Performance and Portable Convolution Operators for ARM-based Multicore Processors

The considerable impact of Convolutional Neural Networks on many Artific...

0 Pablo San Juan, et al. ∙

∙ 05/12/2020

DMR API: Improving cluster productivity by turning applications into malleable

Adaptive workloads can change on–the–fly the configuration of their jobs...

0 Sergio Iserte, et al. ∙

∙ 06/03/2019

Exploiting nested task-parallelism in the ℋ-LU factorization

We address the parallelization of the LU factorization of hierarchical m...

0 Rocío Carratalá-Sáez, et al. ∙

∙ 04/19/2018

Programming Parallel Dense Matrix Factorizations with Look-Ahead and OpenMP

We investigate a parallelization strategy for dense matrix factorization...

0 Sandra Catalán, et al. ∙

∙ 09/01/2017

Look-Ahead in the Two-Sided Reduction to Compact Band Forms for Symmetric Eigenvalue Problems and the SVD

We address the reduction to compact band forms, via unitary similarity t...

0 Rafael Rodríguez-Sánchez, et al. ∙

∙ 11/19/2016

A Case for Malleable Thread-Level Linear Algebra Libraries: The LU Factorization with Partial Pivoting

We propose two novel techniques for overcoming load-imbalance encountere...

0 Sandra Catalán, et al. ∙

∙ 11/06/2015

Multi-Threaded Dense Linear Algebra Libraries for Low-Power Asymmetric Multicore Processors

Dense linear algebra libraries, such as BLAS and LAPACK, provide a relev...

0 Sandra Catalán, et al. ∙

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