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GAROP: Genetic Algorithm framework for Running On Parallel environments

Tomoyuki Hiroyasu, Ryosuke Yamanaka, Masato Yoshimi, Mitsunori Miki

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, Tesla C2050

September 1, 2012 by hgpu

An Implementation of Coincidence Algorithm on Graphic Processing Units

Thitipan Tongsiri, Prabhas Chongstitvatana

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 280

August 27, 2012 by hgpu

Multi-GPU Island-Based Genetic Algorithm for Solving the Knapsack Problem

Jiri Jaros

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Tags: Algorithms, Computer science, CUDA, Genetic programming, GPU cluster, MPI, nVidia, nVidia GeForce GTX 580, Package

June 26, 2012 by hgpu

Automatic Discovery of Algorithms for Multi-Agent Systems

Sjors van Berkel, Daniel Turi, Andrei Pruteanu, Stefan Dulman

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, Search strategies

May 9, 2012 by hgpu

A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark

Jiri Jaros, Petr Pospichal

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Package, Performance

May 2, 2012 by hgpu

Genetic Algorithm Modeling with GPU Parallel Computing Technology

S. Cavuoti, M. Garofalo, M. Brescia, A. Pescape, G. Longo, G. Ventre

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Tags: Algorithms, Astrophysics, Computer science, CUDA, Data mining, Genetic programming, Machine learning, nVidia, nVidia GeForce GT 540 M

April 21, 2012 by hgpu

A parallel Genetic Programming algorithm for classification

Alberto Cano, Amelia Zafra, Sebastian Ventura

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 480

January 11, 2012 by hgpu

Implementing Genetic Algorithms to CUDA Environment Using Data Parallelization

Masashi Oiso, Yoshiyuki Matsumura, Toshiyuki Yasuda, Kazuhiro Ohkura

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 280

January 11, 2012 by hgpu

Hyper neural network on OpenCL

Frantisek Sindelar

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Tags: Algorithms, Compression, Computer science, Genetic programming, Neural networks, nVidia, nVidia Quadro NVS 140 M, OpenCL, Thesis

January 6, 2012 by hgpu

A Framework for Genetic Algorithms in Parallel Environments

Tomoyuki Hiroyasu, Ryosuke Yamanaka, Masato Yoshimi, Mitsunori Miki

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 250

December 20, 2011 by hgpu

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Petr Pospichal, Eoin Murphy, Michael O'Neill, Josef Schwarz, Jiri Jaros

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Genetic programming, Java, nVidia, nVidia GeForce GTX 480, Optimization

December 19, 2011 by hgpu

Minimising Testing in Genetic Programming

W. B. Langdon

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, Software Engineering

December 15, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

GAROP: Genetic Algorithm framework for Running On Parallel environments

An Implementation of Coincidence Algorithm on Graphic Processing Units

Multi-GPU Island-Based Genetic Algorithm for Solving the Knapsack Problem

Automatic Discovery of Algorithms for Multi-Agent Systems

A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark

Genetic Algorithm Modeling with GPU Parallel Computing Technology

A parallel Genetic Programming algorithm for classification

Implementing Genetic Algorithms to CUDA Environment Using Data Parallelization

Hyper neural network on OpenCL

A Framework for Genetic Algorithms in Parallel Environments

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Minimising Testing in Genetic Programming

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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