Banca de DEFESA: HENRIQUE CORREIA TORRES SANTOS

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : HENRIQUE CORREIA TORRES SANTOS
DATE: 17/02/2023
TIME: 14:00
LOCAL: https://meet.google.com/dpk-nexk-mfk
TITLE:

Parallelization and Distribution Instrument for Sequential Simulations Computationals

KEY WORDS:

Desktop grid, Parallel Programing, Distributed Computing, Container Virtualization.

PAGES: 96
BIG AREA: Ciências Agrárias
AREA: Agronomia
SUMMARY:

The need for access to 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. However, the cost of accessing these resources can limit the profile of users who can access them, setting aside various studies that could be carried out in a simpler infrastructure. Furthermore, with the complexity increase of the problems to be solved in research activities through the development of computer simulations, advanced features of parallel and distributed programming have become a requirement for these simulations to be executed promptly. The existing gap in the statistics undergraduate courses syllabus 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 sequentially. 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 simulations on computers available in a 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 various other studies that benefited from using PESC.

COMMITTEE MEMBERS:
Externo ao Programa - 1492798 - ANTONIO RODRIGUES DE CASTRO ROMAGUERA - nullInterno - BORKO STOSIC
Externo à Instituição - RÔMULO CÉSAR CARVALHO DE ARAÚJO - IFPE
Presidente - TIAGO ALESSANDRO ESPINOLA FERREIRA
Externo ao Programa - 2019398 - VICTOR WANDERLEY COSTA DE MEDEIROS - null