high performance computing on graphics processing units: hgpu.org

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hgpu.org » Programming » OpenCL

Bridging the GPGPU-FPGA efficiency gap

Christopher W. Fletcher, Ilia A. Lebedev, Narges B. Asadi, Daniel R. Burke, John Wawrzynek

Tags: Algorithms, Bayesian, Computer science, FPGA, Heterogeneous systems, nVidia, OpenCL

March 22, 2011 by hgpu

Using Parallel Computing for the Display and Simulation of the Space Debris Environment

M. Mockel, C. Wiedemann, S. Flegel, J. Gelhaus, P. Vorsmann, H. Klinkrad, H. Krag

Tags: Earth and Space Sciences, OpenCL, Review, Visualization

March 18, 2011 by hgpu

A Package for OpenCL Based Heterogeneous Computing on Clusters with Many GPU Devices

Amnon Barak, Tal Ben-nun, Ely Levy, Amnon Shiloh

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Tags: Computer science, GPU cluster, nVidia, nVidia GeForce GTX 480, OpenCL, OpenMP

March 15, 2011 by hgpu

Handbook of open source tools

Sandeep Koranne

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, Pthreads

February 26, 2011 by hgpu

Achieving a single compute device image in OpenCL for multiple GPUs

Jungwon Kim, Honggyu Kim, Joo H. Lee, Jaejin Lee

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, Optimization

February 25, 2011 by hgpu

Probing biomolecular machines with graphics processors

James C. Phillips, John E. Stone

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Tags: Biology, Biomolecules, CUDA, GPU cluster, Molecular simulation, nVidia, OpenCL, Review, Tesla S1070

February 23, 2011 by hgpu

Efficient compilation of fine-grained SPMD-threaded programs for multicore CPUs

John A. Stratton, Vinod Grover, Jaydeep Marathe, Bastiaan Aarts, Mike Murphy, Ziang Hu, Wen-mei W. Hwu

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenCL, Programming techniques

February 20, 2011 by hgpu

Decoupled Access/Execute Metaprogramming for GPU-Accelerated Systems

Lee Howes, Anton Lokhmotov, Paul H.J. Kelly, Alastair F. Donaldson

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Tags: CUDA, Filtering, Image processing, nVidia, nVidia GeForce GTX 280, OpenCL

February 19, 2011 by hgpu

High Performance Relevance Vector Machine on GPUs

Depeng Yang, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL

February 19, 2011 by hgpu

A Generic Approach for Developing Highly Scalable Particle-Mesh Codes for GPUs

W. Honig, F. Schmitt, R. Widera, H. Burau, G. Juckeland, M. S. Muller, and M. Bussmann

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Tags: ATI Radeon HD 5770, Computer science, CUDA, nVidia, OpenCL, Particle-in-cell methods, Plasma physics, Tesla C2050, Tesla S1070

February 19, 2011 by hgpu

Performance Comparison of Cholesky Decomposition on GPUs and FPGAs

Depeng Yang, Junqing Sun, JunKu Lee, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, FPGA, Matrix decomposition, nVidia, nVidia GeForce GTX 480, OpenCL, Performance

February 18, 2011 by hgpu

OpenCL Evaluation for Numerical Linear Algebra Library Development

Peng Du, Piotr Luszczek, Jack Dongarra

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Tags: ATI Radeon HD 5870, Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Performance, Tesla C2050

February 17, 2011 by hgpu

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

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Bridging the GPGPU-FPGA efficiency gap

Using Parallel Computing for the Display and Simulation of the Space Debris Environment

A Package for OpenCL Based Heterogeneous Computing on Clusters with Many GPU Devices

Handbook of open source tools

Achieving a single compute device image in OpenCL for multiple GPUs

Probing biomolecular machines with graphics processors

Efficient compilation of fine-grained SPMD-threaded programs for multicore CPUs

Decoupled Access/Execute Metaprogramming for GPU-Accelerated Systems

High Performance Relevance Vector Machine on GPUs

A Generic Approach for Developing Highly Scalable Particle-Mesh Codes for GPUs

Performance Comparison of Cholesky Decomposition on GPUs and FPGAs

OpenCL Evaluation for Numerical Linear Algebra Library Development

Recent source codes

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

ROCm's implementation of Gromacs

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

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