high performance computing on graphics processing units: hgpu.org

hgpu.org » Algorithms

Acceleration of genetic algorithms for sudoku solution on many-core processors

Yuji Sato, Naohiro Hasegawa, Mikiko Sato

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Tags: Algorithms, Computer science, CUDA, Games, Genetic programming, nVidia, nVidia GeForce GTX 460, Presentation

September 20, 2011 by hgpu

Parallel divide-and-evolve: experiments with OpenMP on a multicore machine

Caner Candan, Johann Dreo, Pierre Saveant, Vincent Vidal

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Tags: Algorithms, Artificial intelligence, Computer science, Evolutionary Computations, Metaheuristics, Programming techniques

September 19, 2011 by hgpu

DAMS: distributed adaptive metaheuristic selection

Bilel Derbel, Sebastien Verel

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Tags: Algorithms, Computer science, Metaheuristics, Optimization, Presentation

September 19, 2011 by hgpu

Real-time ray casting of algebraic B-spline surfaces

Feifei Wei, Jieqing Feng

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Interactive application, nVidia, nVidia GeForce GTX 570, Rasterization, Real-time graphics, Visualization

September 19, 2011 by hgpu

Improving SIMD efficiency for parallel Monte Carlo light transport on the GPU

Dietger van Antwerpen

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing

September 19, 2011 by hgpu

Randomized selection on the GPU

Laura Monroe, Joanne Wendelberger, Sarah Michalak

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, nVidia Quadro FX 5000, nVidia Quadro FX 6000, Optimization, Presentation, Probability, Programming techniques

September 19, 2011 by hgpu

Hybrid smoothed particle hydrodynamics

Karthik Raveendran, Chris Wojtan, Greg Turk

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Tags: 3D Graphics and Realism, Algorithms, Computer science, Fluid simulation, Particle simulation

September 19, 2011 by hgpu

Simpler and faster HLBVH with work queues

Kirill Garanzha, Jacopo Pantaleoni, David McAllister

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing, Real-time graphics

September 19, 2011 by hgpu

A GPU-tailored approach for training kernelized SVMs

Andrew Cotter, Nathan Srebro, Joseph Keshet

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Source codes

Tags: Algorithms, Clustering, Computer science, nVidia, Optimization, Package, Performance, Programming techniques, Tesla C1060

September 19, 2011 by hgpu

Stream computing on graphics hardware

Ian Buck

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Tags: Algorithms, ATI, ATI Radeon X800 XT, Benchmarking, Brook, Compilers, Computer science, nVidia, nVidia GeForce 6800, Review, Thesis

September 19, 2011 by hgpu

Using many-core hardware to correlate radio astronomy signals

Rob V. van Nieuwpoort, John W. Romein

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Tags: Algorithms, Astrophysics, ATI, ATI CAL, ATI Radeon HD 4870, ATI Stream, Cell processor, CUDA, nVidia, Performance, Physics, Signal processing, Tesla C1060

September 19, 2011 by hgpu

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Amol Ghoting, Prabhanjan Kambadur, Edwin Pednault, Ramakrishnan Kannan

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Tags: Algorithms, Computer science, Data mining, Machine learning, MapReduce, MPI, OpenCL, Performance, Software Engineering

September 16, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Acceleration of genetic algorithms for sudoku solution on many-core processors

Parallel divide-and-evolve: experiments with OpenMP on a multicore machine

DAMS: distributed adaptive metaheuristic selection

Real-time ray casting of algebraic B-spline surfaces

Improving SIMD efficiency for parallel Monte Carlo light transport on the GPU

Randomized selection on the GPU

Hybrid smoothed particle hydrodynamics

Simpler and faster HLBVH with work queues

A GPU-tailored approach for training kernelized SVMs

Stream computing on graphics hardware

Using many-core hardware to correlate radio astronomy signals

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

Most viewed papers (last 30 days)