high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce GTX 480

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Shuai Che, Jeremy W. Sheaffer, Kevin Skadron

View

Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, Performance

October 15, 2011 by hgpu

Speeding up the MATLAB complex networks package using graphic processors

Zhang Bai-Da, Tang Yu-Hua, Wu Jun-Jie, Li Xin

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Networks, nVidia, nVidia GeForce GTX 480

October 15, 2011 by hgpu

Developing a High Performance GPGPU Compiler Using Cetus

Yi Yang, Huiyang Zhou

View

Download (PDF)

Source codes

Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 5870, Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization

October 13, 2011 by hgpu

General purpose computing on graphics processing units using OpenCL

Mats Johansson, Oscar Winter

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 4870, ATI Stream, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 480, OpenCL, Optical flow, Optimization, Thesis

October 12, 2011 by hgpu

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

Peter Zinterhof

View

Download (PDF)

Tags: Algorithms, Computational Complexity, Computer science, Nearest neighbour, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, OpenCL, OpenMPI, Search, Tesla C2050

October 10, 2011 by hgpu

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

Alejandro C. Crespo, Jose M. Dominguez, Anxo Barreiro, Moncho Gomez-Gesteira, Benedict D. Rogers

View

Download (PDF)

Source codes

Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance, Tesla M1060, Visualization

October 10, 2011 by hgpu

Parallel and efficient Boolean on polygonal solids

H. Zhao, C. C. L. Wang, Y. Chen, X. Jin

View

Download (PDF)

Tags: Computer science, CUDA, Image processing, nVidia GeForce GTX 480

October 9, 2011 by hgpu

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

W.J. Palenstijna, K.J. Batenburga, J. Sijbersa

View

Download (PDF)

Tags: Biology, Image reconstruction, Medicine, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Tomography

October 8, 2011 by hgpu

Connected-component identification and cluster update on graphics processing units

Martin Weigel

View

Download (PDF)

Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla M2070

October 6, 2011 by hgpu

Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations

Paul Richmond, Lars Buesing, Michele Giugliano, Eleni Vasilaki

View

Download (PDF)

Source codes

Tags: Biology, CUDA, Neuroscience, nVidia, nVidia GeForce GTX 480, Package, Python

October 5, 2011 by hgpu

Flexible, high performance convolutional neural networks for image classification

Dan C. Ciresan, Ueli Meier, Jonathan Masci, Luca M. Gambardella, Jurgen Schmidhuber

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580

October 5, 2011 by hgpu

GPU performance comparison for accelerated radar data processing

Chris Fallen, Beau Bellamy, Greg Newby, Brent Watkins

View

Download (PDF)

Tags: Measurement techniques, nVidia, nVidia GeForce GTX 480, OpenCL, Presentation, Signal processing, Tesla M2050

October 4, 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

* * *

high performance computing on graphics processing units: hgpu.org

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Speeding up the MATLAB complex networks package using graphic processors

Developing a High Performance GPGPU Compiler Using Cetus

General purpose computing on graphics processing units using OpenCL

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

Parallel and efficient Boolean on polygonal solids

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

Connected-component identification and cluster update on graphics processing units

Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations

Flexible, high performance convolutional neural networks for image classification

GPU performance comparison for accelerated radar data processing

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

Most viewed papers (last 30 days)