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Evolving GeneChip correlation predictors on parallel graphics hardware

William B. Langdon

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Tags: Bioinformatics, Computer science, Genetic programming, nVidia, nVidia GeForce 8800 GTX, OpenGL, Package, RapidMind

January 21, 2011 by hgpu

Evolving a CUDA kernel from an nVidia template

William B. Langdon, Mark Harman

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Tags: Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295

January 21, 2011 by hgpu

Genetic Programming An Introductory Tutorial and a Survey of Techniques and Applications

Riccardo Poli, William B. Langdon, Nicholas F. McPhee, John R. Koza

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Tags: Algorithms, Computer science, Genetic programming, nVidia, OpenGL, RapidMind

January 21, 2011 by hgpu

A Field Guide to Genetic Programming

Riccardo Poli, William B. Langdon, Nicholas F. McPhee

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Tags: Algorithms, Book, Computer science, Genetic programming, nVidia

January 21, 2011 by hgpu

A CUDA SIMT interpreter for genetic programming. Revised

William B. Langdon

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Tags: Computer science, CUDA, Genetic programming, nVidia, Package, Tesla T10P

January 21, 2011 by hgpu

Accelerating Genetic Programming through Graphics Processing Units

Wolfgang Banzhaf, Simon Harding, William B. Langdon and Garnett Wilson

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Tags: Computer science, Genetic programming, HLSL, nVidia, nVidia GeForce 8800 GTX, RapidMind, Xbox 360

January 21, 2011 by hgpu

A Many Threaded CUDA Interpreter for Genetic Programming

William B. Langdon

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Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, Package

January 21, 2011 by hgpu

Large Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units

William B. Langdon

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Tags: Computer science, Genetic programming, nVidia, nVidia GeForce 8800 GTX, OpenGL, Package, RapidMind

January 21, 2011 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Evolving GeneChip correlation predictors on parallel graphics hardware

Evolving a CUDA kernel from an nVidia template

Genetic Programming An Introductory Tutorial and a Survey of Techniques and Applications

A Field Guide to Genetic Programming

A CUDA SIMT interpreter for genetic programming. Revised

Accelerating Genetic Programming through Graphics Processing Units

A Many Threaded CUDA Interpreter for Genetic Programming

Large Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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