high performance computing on graphics processing units: hgpu.org

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Generating Device-specific GPU code for Local Operators in Medical Imaging

Richard Membarth, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Code generation, CUDA, Image processing, Medicine, nVidia, nVidia Quadro FX 5800, OpenCL, RapidMind, Tesla C2050

June 1, 2012 by hgpu

Large-scale Nanostructure Simulations from X-ray Scattering Data On Graphics Processor Clusters

Abhinav Sarje, Jack Pien, Xiaoye S. Li, Elaine Chan, Slim Chourou, Alexander Hexemer, Arthur Scholz and Edward Kramer

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Tags: Algorithms, CUDA, GPU cluster, Monte Carlo simulation, MPI, nVidia, Optimization, Physics, Tesla C2050, Tesla M2090

May 30, 2012 by hgpu

GPU-accelerated simulation of colloidal suspensions with direct hydrodynamic interactions

Michael Kopp, Felix Hofling

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Tags: Algorithms, Computational Physics, CUDA, Molecular dynamics, nVidia, Package, Physics, Tesla C2050, Tesla S1070

May 30, 2012 by hgpu

CUDA Based Enhanced Differential Evolution: a Computational Analysis

Donald Davendra, Jan Gaura, Magdalena Bialic-Davendra, Roman Senkerik

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

May 20, 2012 by hgpu

An MPI-CUDA Implementation and Optimization for Parallel Sparse Equations and Least Squares (LSQR)

He Huang, Liqiang Wang, En-Jui Lee, Po Chen

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Tags: Computer science, CUBLAS, CUDA, Earth and Space Sciences, Geoscience, MPI, nVidia, Optimization, Tesla C2050, Tesla M2070

May 19, 2012 by hgpu

Accurate CUDA Performance Modeling for Sparse Matrix-Vector Multiplication

Ping Guo, Liqiang Wang

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 19, 2012 by hgpu

b-Bit Minwise Hashing in Practice: Large-Scale Batch and Online Learning and Using GPUs for Fast Preprocessing with Simple Hash Functions

Ping Li, Anshumali Shrivastava, Arnd Christian Konig

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Tags: Algorithms, Computer science, CUDA, Databases, Hashing, Information Retrieval, nVidia, Tesla C2050

May 16, 2012 by hgpu

The BiConjugate gradient method on GPUs

G. Ortega, E. M. Garzon, F. Vazquez, I. Garcia

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 15, 2012 by hgpu

Scalable Distributed Fast Multipole Methods

Qi Hu, Nail A. Gumerov, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, Heterogeneous systems, Numerical simulation, nVidia, Tesla C2050

May 12, 2012 by hgpu

Multi-dimensional characterization of electrostatic surface potential computation on graphics processors

Mayank Daga, Wu-chun Feng

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Tags: Algorithms, Biology, Biomolecules, Computational Complexity, CUDA, Electrostatics, Molecular modeling, nVidia, Optimization, Tesla C1060, Tesla C2050

May 12, 2012 by hgpu

Enhancing GPU Parallelism in Nature-Inspired Algorithms

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

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Tags: Algorithms, Computational modelling, Computer science, CUDA, Data parallelism, nVidia, Optimization, P systems, Tesla C1060, Tesla C2050

May 12, 2012 by hgpu

Enhancing data parallelism for Ant Colony Optimization 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, nVidia, Optimization, Tesla C2050

May 10, 2012 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

Generating Device-specific GPU code for Local Operators in Medical Imaging

Large-scale Nanostructure Simulations from X-ray Scattering Data On Graphics Processor Clusters

GPU-accelerated simulation of colloidal suspensions with direct hydrodynamic interactions

CUDA Based Enhanced Differential Evolution: a Computational Analysis

An MPI-CUDA Implementation and Optimization for Parallel Sparse Equations and Least Squares (LSQR)

Accurate CUDA Performance Modeling for Sparse Matrix-Vector Multiplication

b-Bit Minwise Hashing in Practice: Large-Scale Batch and Online Learning and Using GPUs for Fast Preprocessing with Simple Hash Functions

The BiConjugate gradient method on GPUs

Scalable Distributed Fast Multipole Methods

Multi-dimensional characterization of electrostatic surface potential computation on graphics processors

Enhancing GPU Parallelism in Nature-Inspired Algorithms

Enhancing data parallelism for Ant Colony Optimization on GPUs

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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