high performance computing on graphics processing units: hgpu.org

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Parallel Implementations of a Disparity Estimation Algorithm Based on a Proximal Splitting Method

R. Gaetano, G. Chierchia, B. Pesquet-Popescu

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Tags: Algorithms, Computer science, nVidia, OpenCL, Optimization, Stereo vision, Tesla C1060

May 9, 2013 by hgpu

Directive-based Approach to Heterogeneous Computing

Ruyman Reyes Castro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Package, Python, Tesla C1060, Thesis

April 25, 2013 by hgpu

Automatic Parallelization of a Gap Model using Java and OpenCL

Jonathan Passerat-Palmbach, Arthur Forest, Julien Pal, Bruno Corbara, D.R.C. Hill

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Tags: Computer science, Java, nVidia, nVidia GeForce GTX 590, OpenCL, Tesla C1060, Tesla C2050

April 22, 2013 by hgpu

High Performance FFT Based Poisson Solver on a CPU-GPU Heterogeneous Platform

Jing Wu, Joseph JaJa

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Tags: CUDA, FFT, Heterogeneous systems, nVidia, Tesla C1060

April 13, 2013 by hgpu

High Performance Computing on GPU for Electromagnetic Logging

V.N. Glinskikh, A.E. Kontorovich, M.I. Epov

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Tags: Algorithms, CUDA, Electrodynamics, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 460, Tesla C1060

April 12, 2013 by hgpu

Accelerating Image Reconstruction in Three-Dimensional Optoacoustic Tomography on Graphics Processing Units

Kun Wang, Chao Huang, Yu-Jiun Kao, Cheng-Ying Chou, Alexander A. Oraevsky, Mark A. Anastasio

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Tags: CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C1060, Tesla C2050, Tomography

April 9, 2013 by hgpu

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

R. Capuzzo-Dolcettaa, M. Spera

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Tags: Astrophysics, ATI, ATI Radeon HD 6970, ATI Radeon HD 7870, ATI Radeon HD 7970, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Tesla C1060, Tesla C2050, Tesla K20

April 9, 2013 by hgpu

pVOCL: Power-Aware Dynamic Placement and Migration in Virtualized GPU Environments

Palden Lama, Yan Li, Ashwin M. Aji, Pavan Balaji, James Dinan, Shucai Xiao, Yunquan Zhang, Wu-chun Feng, Rajeev Thakur, Xiaobo Zhou

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Tags: Computer science, Energy-efficient computing, nVidia, OpenCL, Tesla C1060, Virtualization

April 8, 2013 by hgpu

Solving RFIC Simulation Tasks Using GPU Computations

Mihail-Iulian Andrei, Sebastian Kula

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Tags: Algorithms, CUDA, Electrodynamics, FEM, Finite element method, Linear Algebra, nVidia, Tesla C1060, Tesla C2070

April 1, 2013 by hgpu

A Massively Parallel Associative Memory Based on Sparse Neural Networks

Zhe Yao, Vincent Gripon, Michael G. Rabbat

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Tags: Artificial intelligence, Computer science, CUDA, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla C1060

March 31, 2013 by hgpu

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Sergio Bernabe, Sergio Sanchez, Antonio Plaza, Sebastian Lopez, Jon Atli Benediktsson, Roberto Sarmiento

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Tags: Algorithms, CUBLAS, CUDA, Image processing, nVidia, nVidia GeForce GTX 580, Tesla C1060

March 26, 2013 by hgpu

Real-Time Implementation of the Pixel Purity Index Algorithm for Endmember Identification on GPUs

Xianyun Wu, Bormin Huang, Antonio Plaza, Yunsong Li, Chengke Wu

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Tags: Algorithms, Computational Complexity, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 590, Tesla C1060

March 23, 2013 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

Parallel Implementations of a Disparity Estimation Algorithm Based on a Proximal Splitting Method

Directive-based Approach to Heterogeneous Computing

Automatic Parallelization of a Gap Model using Java and OpenCL

High Performance FFT Based Poisson Solver on a CPU-GPU Heterogeneous Platform

High Performance Computing on GPU for Electromagnetic Logging

Accelerating Image Reconstruction in Three-Dimensional Optoacoustic Tomography on Graphics Processing Units

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

pVOCL: Power-Aware Dynamic Placement and Migration in Virtualized GPU Environments

Solving RFIC Simulation Tasks Using GPU Computations

A Massively Parallel Associative Memory Based on Sparse Neural Networks

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Real-Time Implementation of the Pixel Purity Index Algorithm for Endmember Identification 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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