Oscar A. Esquivel-Flores
Oscar A. Esquivel-Flores received his Bachelor's degree in Applied Mathematics and Computing from Universidad Nacional Autónoma de México (UNAM). M.S. degree in Computer Sciences from Universidad Autónoma Metropolitana, México and PhD degree in Computer Engineering from UNAM in 2013. He has working on parallel and high performance computing as part of a posdoctoral position at the Barcelona Supercomputing Center as an international agreement with National Council of Science and Technology of México. He currently helds a research position in Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas at Universidad Nacional Autónoma de México developing parallel algorithms regard matrix computations, machine learning and optimization.
Sessions
This work presents a parallel implementation of Monte Carlo-Markov Chain method for solving systems of linear algebraic equations using Julia and GPU accelerator. Julia 1.1.0 + CUDAnative.jl provide several advantages regarding development and performance which help to delve into convergence and precision analysis. This work is supported by PAPIIT-IA104720.