high performance computing on graphics processing units: hgpu.org

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Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Rajesh Bordawekar, Uday Bondhugula, Ravi Rao

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Performance, Programming techniques

February 26, 2011 by hgpu

Concurrent GPU Programming

Lesley Northam

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 M GTX, Programming techniques, Review

February 26, 2011 by hgpu

Pyramid Methods in GPU-Based Image Processing

Magnus Strengert, Martin Kraus, and Thomas Ertl

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Tags: Algorithms, Image processing, nVidia, nVidia GeForce 7800 GTX, OpenGL, Programming techniques

February 25, 2011 by hgpu

Program Optimization Study on a 128-Core GPU

Shane Ryoo, Christopher I. Rodrigues, Sam S. Stone, Sara S. Baghsorkhi, Sain-Zee Ueng, and Wen-mei W. Hwu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Programming techniques

February 20, 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

Accelerating Cosmological Data Analysis with Graphics Processors

Dylan W. Roeh, Volodymyr V. Kindratenko, Robert J. Brunner

Tags: Astrophysics, Cosmology, CUDA, GPU cluster, MPI, nVidia, Physics, Programming techniques

February 15, 2011 by hgpu

Partitioning streaming parallelism for multi-cores: a machine learning based approach

Zheng Wang, Michael F. P. O'Boyle

Tags: Computer science, Optimization, Programming techniques

February 8, 2011 by hgpu

XMT-GPU: A PRAM Architecture for Graphics Computation

Thomas M. DuBois, Bryant Lee, Yi Wang, Marc Olano, Uzi Vishkin

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Tags: Algorithms, ATI, ATI Radeon X700 Pro, Computer science, nVidia, nVidia GeForce 7900 GTX, nVidia GeForce 8800 GTX, OpenGL, Programming techniques

February 6, 2011 by hgpu

Evaluating multi-core platforms for HPC data-intensive kernels

Alexander S. van Amesfoort, Ana Lucia Varbanescu, Henk J. Sips, Rob V. van Nieuwpoort

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Tags: Algorithms, Cell processor, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Programming techniques, Tesla C1060

February 6, 2011 by hgpu

Cortical architectures on a GPGPU

Andrew Nere, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Image recognition, nVidia, Programming techniques, Tesla C1060

February 2, 2011 by hgpu

OpenGL(R) ES 2.0 Programming Guide

Aaftab Munshi, Dan Ginsburg, Dave Shreiner

Tags: Book, Computer science, OpenGL, Programming techniques, Tutorial

February 2, 2011 by hgpu

OpenGL SuperBible: Comprehensive Tutorial and Reference (5th Edition)

Richard S. Wright, Nicholas Haemel, Graham Sellers, Benjamin Lipchak

Tags: Book, Computer science, OpenGL, Programming techniques, Tutorial

February 2, 2011 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

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Concurrent GPU Programming

Pyramid Methods in GPU-Based Image Processing

Program Optimization Study on a 128-Core GPU

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

Accelerating Cosmological Data Analysis with Graphics Processors

Partitioning streaming parallelism for multi-cores: a machine learning based approach

XMT-GPU: A PRAM Architecture for Graphics Computation

Evaluating multi-core platforms for HPC data-intensive kernels

Cortical architectures on a GPGPU

OpenGL(R) ES 2.0 Programming Guide

OpenGL SuperBible: Comprehensive Tutorial and Reference (5th Edition)

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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