high performance computing on graphics processing units: hgpu.org

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Graphics processing unit (GPU) programming strategies and trends in GPU computing

Andre R. Brodtkorb, Trond R. Hagen, Martin L. Saetra

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Tags: Computer science, Heterogeneous systems, Metaheuristics, Optimization, Overview, Programming techniques

April 19, 2013 by hgpu

Parallelization of the Cuckoo Search using CUDA Architecture

Raka Jovanovic, Milan Tuba

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 540 M, Optimization

April 1, 2013 by hgpu

Many-threaded Differential Evolution on the GPU

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Computer science, CUDA, Differential evolution, Metaheuristics, nVidia, Tesla C2050

January 30, 2013 by hgpu

GPU-based tuning of quantum-inspired genetic algorithm for a combinatorial optimization problem

R. Nowotniak, J. Kucharski

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 295, Optimization

September 27, 2012 by hgpu

A GPU implementation of the Simulated Annealing Heuristic for the Quadratic Assignment Problem

Gerald Paul

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Tags: Computer science, CUDA, Metaheuristics, nVidia, Tesla C2070

August 14, 2012 by hgpu

Solving the Flexible Job Shop Problem on Multi-GPU

Wojciech Bozejko, Zdzilaw Hejducki, Mariusz Uchronski, Mieczyslaw Wodecki

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Tags: Computer science, CUDA, GPU cluster, Metaheuristics, MPI, nVidia, Optimization, Search, Tesla S2050

August 8, 2012 by hgpu

Parallel GPU Implementation of Iterated Local Search for the Travelling Salesman Problem

Audrey Delevacq, Pierre Delisle, Michael Krajecki

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, Tesla C2050

August 4, 2012 by hgpu

A Parallel Ant Colony Optimization Algorithm for the Travelling Salesman Problem: Improving Performance Using CUDA

Octavian Nitica

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, Optimization, Tesla C1060, Tesla C2050, Tesla C870, Thesis

January 26, 2012 by hgpu

Enhancing Data Parallelism for Ant Colony Optimisation on GPUs

Jose M. Cecilia, Jose M. Garcia, Andy Nisbet, Martyn Amos, Manuel Ujaldon

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Metaheuristics, nVidia, Tesla C2050

January 12, 2012 by hgpu

GPU Computing for Parallel Local Search Metaheuristics

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Optimization, Tesla M2050

January 3, 2012 by hgpu

Towards paradisEO-MO-GPU: a framework for GPU-based local search metaheuristics

N. Melab, T-V. Luong, K. Boufaras, E-G. Talbi

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Source codes

Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 480, Package

November 27, 2011 by hgpu

GPU-based Multi-start Local Search Algorithms

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 280, Optimization, Search

November 22, 2011 by hgpu

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

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high performance computing on graphics processing units: hgpu.org

Graphics processing unit (GPU) programming strategies and trends in GPU computing

Parallelization of the Cuckoo Search using CUDA Architecture

Many-threaded Differential Evolution on the GPU

GPU-based tuning of quantum-inspired genetic algorithm for a combinatorial optimization problem

A GPU implementation of the Simulated Annealing Heuristic for the Quadratic Assignment Problem

Solving the Flexible Job Shop Problem on Multi-GPU

Parallel GPU Implementation of Iterated Local Search for the Travelling Salesman Problem

A Parallel Ant Colony Optimization Algorithm for the Travelling Salesman Problem: Improving Performance Using CUDA

Enhancing Data Parallelism for Ant Colony Optimisation on GPUs

GPU Computing for Parallel Local Search Metaheuristics

Towards paradisEO-MO-GPU: a framework for GPU-based local search metaheuristics

GPU-based Multi-start Local Search Algorithms

Recent source codes

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

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