Minicursos do SSCAD 2024

Autores

Arthur F. Lorenzon (ed)
UFRGS
Álvaro Luiz Fazenda (ed)
UNIFESP

Palavras-chave:

Big Data, Aprendizado de Máquina, Interface Myriad, HPCC Systems, Perfilamento, Escalabilidade, Aplicações Paralelas, Parallel Scalability Suite, Programação Paralela, MPI, OpenMP Offloading, Simulação Arquitetural, gem5, Computação Quântica, IBM/Qiskit, Análise e Otimização de Programas

Sinopse

Esta edição do Livro de Minicursos do SSCAD traz seis minicursos apresentados durante o XXV Simpósio em Sistemas Computacionais de Alto Desempenho, realizado entre os dias 23 e 25 de outubro de 2024 em São Carlos, SP. O primeiro capítulo versa sobre conceitos essenciais de processamento e análise de volumes massivos de dados, fazendo uso de algoritmos de aprendizado de máquina de forma prática na plataforma HPCC (High Performance Computing Cluster). Já no segundo capítulo, é apresentada ao leitor a possibilidade de compreender o Parallel Scalability Suite para avaliar o comportamento de aplicações paralelas mediante perfilamento e visualização da escalabilidade. O terceiro capítulo, por sua vez, apresenta técnicas de programação paralela híbridas aderentes ao padrão MPI e OpenMP Offloading, com ênfase nos modelos de paralelismo em aceleradores. No quarto capítulo, conceitos fundamentais de simulação arquitetural com o simulador gem5 são introduzidos. O capítulo também explora como a simulação habilita os projetistas a explorar, verificar e otimizar arquiteturas através da modelagem de seu comportamento e interação com componentes chaves do sistema. Considerando os avanços da computação quântica, o capítulo 5 demonstra como desenvolver algoritmos para uma arquitetura de computação quântica através do kit de desenvolvimento usando o IBM/Qiskit. Por fim, o sexto capítulo estuda as definições sobre análise de desempenho, as principais técnicas utilizadas e algumas das ferramentas para analisar o desempenho de aplicações paralelas.

Capítulos

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Data de publicação

23/10/2024

Licença

Creative Commons License
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.

Detalhes sobre o formato disponível para publicação: Volume Completo

Volume Completo

ISBN-13 (15)

978-85-7669-610-0