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EvoTorch: Scalable Evolutionary Computation in Python

Nihat Engin Toklu, Timothy Atkinson, Vojtěch Micka, Paweł Liskowski, Rupesh Kumar Srivastava

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Tags: Artificial intelligence, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, Package, Python, PyTorch, Tesla V100

March 5, 2023 by hgpu

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Jhe-Yu Liou, Muaaz Awan, Steven Hofmeyr, Stephanie Forrest, Carole-Jean Wu

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Tags: Bioinformatics, Biology, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti, Package, performance portability, Sequence alignment, Tesla P100, Tesla V100

September 4, 2022 by hgpu

An Overview on the Latest Nature-Inspired and Metaheuristics-Based Image Registration Algorithms

J. Santamaría, M. L. Rivero-Cejudo, M. A. Martos-Fernández, F. Roca

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Tags: Computer science, Computer vision, Evolutionary Computations, Image registration, Metaheuristics, Neural and Evolutionary Computing, Overview

May 4, 2020 by hgpu

GEVO: GPU Code Optimization using Evolutionary Computation

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

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Tags: Computer science, CUDA, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, Package, PTX, Tesla P100

April 26, 2020 by hgpu

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

Xiangang Li, Xihong Wu

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Tags: Computer science, Evolutionary Computations, Neural and Evolutionary Computing, Neural networks, Speech recognition

October 18, 2014 by hgpu

Solving the Examination Timetabling Problem in GPUs

Vasileios Kolonias, George Goulas, Christos Gogos, Panayiotis Alefragis, Efthymios Housos

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, nVidia, nVidia GeForce GTX 580, Sparse matrix

July 7, 2014 by hgpu

Evolutionary Simulation of Life Using CUDA

Adam Call

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Tags: Computer science, CUDA, Evolutionary Computations, Neural networks, nVidia

May 17, 2014 by hgpu

Genetically Improved CUDA kernels for StereoCamera

W. B. Langdon, M. Harman

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Tags: Computer science, CUDA, Evolutionary Computations, Genetic programming, nVidia, nVidia GeForce GTX 580, Package, Tesla C2050, Tesla K20, Tesla T10

March 12, 2014 by hgpu

Parallel Compact Genetic Algorithm on CUDA-C Platform

Vuppuluri Sumati

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Genetic programming, nVidia

December 21, 2013 by hgpu

libCudaOptimize: an Open Source Library of GPU-based Metaheuristics

Youssef S.G. Nashed, Roberto Ugolotti, Pablo Mesejo, Stefano Cagnoni

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Tags: Artificial intelligence, Computer science, CUDA, Differential evolution, Evolutionary Computations, Metaheuristics, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTS 450, Optimization, Package, Particle swarm optimization

June 21, 2013 by hgpu

Speeding Up Model Building for ECGA on CUDA Platform

Chung-Yu Shao, Tian-Li Yu

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, Tesla C2050

March 9, 2013 by hgpu

Speeding up the evaluation of evolutionary learning systems using GPGPUs

Maria Franco, Natalio Krasnogor, Jaume Bacardit

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Tags: BioHEL, Evolutionary Computations, LCS, Learning Classifier System, Machine learning, Tesla C1060

November 1, 2012 by mariaux

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Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

See all packages

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high performance computing on graphics processing units: hgpu.org

EvoTorch: Scalable Evolutionary Computation in Python

Understanding the Power of Evolutionary Computation for GPU Code Optimization

An Overview on the Latest Nature-Inspired and Metaheuristics-Based Image Registration Algorithms

GEVO: GPU Code Optimization using Evolutionary Computation

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

Solving the Examination Timetabling Problem in GPUs

Evolutionary Simulation of Life Using CUDA

Genetically Improved CUDA kernels for StereoCamera

Parallel Compact Genetic Algorithm on CUDA-C Platform

libCudaOptimize: an Open Source Library of GPU-based Metaheuristics

Speeding Up Model Building for ECGA on CUDA Platform

Speeding up the evaluation of evolutionary learning systems using GPGPUs

Recent source codes

Clava: C/C++ Source-to-Source Tool based on Clang

gpuLik

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

BAT: A standardized benchmark suite for auto-tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

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