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A characterization and analysis of PTX kernels

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, PTX

April 2, 2011 by hgpu

Parallel computing with CUDA

M. Garland

Tags: Computer science, CUDA, nVidia, Programming techniques

April 2, 2011 by hgpu

Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Robert Dietrich, Thomas Ilsche, Guido Juckeland

Tags: Computer science, CUDA, nVidia, OpenCL, Performance

April 1, 2011 by hgpu

Message Passing Interface support for the runtime adaptive multi-processor system-on-chip RAMPSoC

D. Gohringer, M. Hubner, L. Hugot-Derville, J. Becker

Tags: Computer science, CUDA, MPI, nVidia, OpenCL, OpenGL

April 1, 2011 by hgpu

Higher order FEM numerical integration on GPUs with OpenCL

Przemyslaw Plaszewski, Krzysztof Banas, Pawel Maciol

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, nVidia GeForce GTX 285, OpenCL

April 1, 2011 by hgpu

Implementation of Smith-Waterman Algorithm in OpenCL for GPUs

Dzmitry Razmyslovich, Guillermo Marcus, Markus Gipp, Marc Zapatka, Andreas Szillus

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, OpenCL, Poster, Sequence alignment, Smith-Waterman algorithm

March 31, 2011 by hgpu

CUDACL: A tool for CUDA and OpenCL programmers

Ferosh Jacob, David Whittaker, Sagar Thapaliya, Purushotham Bangalore, Marjan Mernik, Jeff Gray

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Tags: Computer science, CUDA, High-level Languages, Java, nVidia, nVidia GeForce GTX 260, OpenCL

March 31, 2011 by hgpu

OpenCL – An effective programming model for data parallel computations at the Cell Broadband Engine

J. Breitbart, C. Fohry

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Tags: Cell processor, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, OpenCL

March 31, 2011 by hgpu

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

Andreas Klockner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih

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Source codes

Tags: Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 9400 M, nVidia GeForce GTX 295, nVidia GeForce GTX 480, OpenCL, Package, PyOpenCL, Python, Software Engineering, Tesla C1060

March 30, 2011 by hgpu

CuHMMer: A load-balanced CPU-GPU cooperative bioinformatics application

Ping Yao, Hong An, Mu Xu, Gu Liu, Xiaoqiang Li, Yaobin Wang, Wenting Han

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce 8800 GTX, Pattern Search

March 29, 2011 by hgpu

Multigrid on GPU: Tackling Power Grid Analysis on parallel SIMT platforms

Zhuo Feng, Peng Li

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Tags: CAD, Computational Engineering, Computer science, CUDA, nVidia, nVidia GeForce 8800 Ultra

March 29, 2011 by hgpu

5.6: GPU enhancement of FDTD-PIC plasma-wave simulations

A.J. Woods, L.D. Ludeking

Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, Plasma physics

March 29, 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

A characterization and analysis of PTX kernels

Parallel computing with CUDA

Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Message Passing Interface support for the runtime adaptive multi-processor system-on-chip RAMPSoC

Higher order FEM numerical integration on GPUs with OpenCL

Implementation of Smith-Waterman Algorithm in OpenCL for GPUs

CUDACL: A tool for CUDA and OpenCL programmers

OpenCL – An effective programming model for data parallel computations at the Cell Broadband Engine

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

CuHMMer: A load-balanced CPU-GPU cooperative bioinformatics application

Multigrid on GPU: Tackling Power Grid Analysis on parallel SIMT platforms

5.6: GPU enhancement of FDTD-PIC plasma-wave simulations

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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