Banca de QUALIFICAÇÃO: HENRIQUE CORREIA TORRES SANTOS

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : HENRIQUE CORREIA TORRES SANTOS
DATE: 17/08/2022
TIME: 14:00
LOCAL: https://meet.google.com/jsm-pzks-qqg
TITLE:

Parallelization and Distribution Instrument for Sequential Simulations Computationals

KEY WORDS:

Distributed Programming, Parallel Programming, Container, Grid

PAGES: 80
BIG AREA: Ciências Agrárias
AREA: Agronomia
SUMMARY:

The need for computational resources grows as the increasing complexity in the development of computational algorithms becomes frequent in different sectors of the scientific community. The search for these resources has stimulated the development of several cloud platforms, which abstract the complexity of a computational infrastructure while offering its users access to the resources needed for their simulations. The cost of accessing these resources can limit the profile of users who can access them, setting aside a variety of studies that could be carried out in a simpler infrastructure. With the increase in the complexity of the problems to be solved in research activities, through the development of computer simulations, advanced features of parallel and distributed programming become a requirement for these simulations to be executed in a timely manner. With the existing gap in the statistics undergraduate courses syllabus it opens space for the development of a solution that allows an abstraction of the complexity of this type of programming, allowing written codes to be executed in a sequential way. run in parallel with minimal tweaks to the original code. In this thesis proposal, we present the Parallel Experiment for Sequential Code (PESC), a platform for distributing computer simulations on computers available in a computer network, packaging the user code in containers that abstract all complexity required to configure an execution environment and allow any user to benefit from this existing infrastructure. With an easy-to-use web module and a client module installed on the computers that will run the simulations, it is possible to run simulations in several programming languages, scripts and frameworks (Python, Java, C, R, PyTorch, Tensorflow, among others). The results are consolidated through the user’s page with runtime statistics and a distribution map of the simulations by the computers. We Will present results obtained in simulations that required more than 1000 runs with different initial parameters and a variety of other studies that benefited from the use of PESC.

BANKING MEMBERS:
Presidente - 1283470 - TIAGO ALESSANDRO ESPINOLA FERREIRA
Interno - 1255603 - BORKO STOSIC
Externo ao Programa - 1492798 - ANTONIO RODRIGUES DE CASTRO ROMAGUERA - UFRPEExterno ao Programa - 2019398 - VICTOR WANDERLEY COSTA DE MEDEIROS - UFRPEExterno à Instituição - RÔMULO CÉSAR CARVALHO DE ARAÚJO - IFPE