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Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review

Suejb Memeti, Sabri Pllana, Alecio Binotto, Joanna Kolodziej, and Ivona Brandic

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Tags: Computer science, Machine learning, Metaheuristics, parallel computing, software optimization

February 10, 2018 by suejb.memeti

Global finite element matrix construction based on a CPU-GPU implementation

Francisco Javier Ramírez-Gil, Marcos de Sales Guerra Tsuzuki, Wilfredo Montealegre-Rubio

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Tags: Analysis of PDEs, Computational Engineering, CUDA, FEM, Numerical Analysis, parallel computing, PDEs, Performance

January 21, 2015 by fjramireg

A Study of Successive Over-relaxation Method Parallelization Over Modern HPC Languages

Sparsh Mittal

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Tags: cpu, multithreading, parallel computing, Parallel programming, Parallelization

November 20, 2014 by sparsh0mittal

Development of High-Performance Software Components for Emerging Architectures

Stefan Lemvig Glimberg, Allan Peter Engsig-Karup, Allan S. Nielsen, Bernd Dammann

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Tags: Computer science, CUDA, GPGPU, iterative methods, Mathematics, multigrid, Package, parallel computing, Partial differential equations, Software development

March 12, 2014 by apek

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

Experiences in Building a Composable and Functional API for Runtime SPIR-V Code Generation

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Descend: A Safe GPU Systems Programming Language

Redwood heterogeneous framework

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

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high performance computing on graphics processing units: hgpu.org

Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review

Global finite element matrix construction based on a CPU-GPU implementation

A Study of Successive Over-relaxation Method Parallelization Over Modern HPC Languages

Development of High-Performance Software Components for Emerging Architectures

Recent source codes

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

AutoDock for GPUs and other accelerators

spotPython: Sequential Parameter Optimization in Python

Test benchmarks for CELERITY

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Redwood heterogeneous framework

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