high performance computing on graphics processing units: hgpu.org

Mark S. Friedrichs, Peter Eastman, Vishal Vaidyanathan, Mike Houston, Scott Legrand, Adam L. Beberg, Daniel L. Ensign, Christopher M. Bruns, Vijay S. Pande

View

Download (PDF)

Source codes

Tags: ATI, ATI Radeon HD 4870, ATI Stream, Biology, Brook, Chemistry, Computational chemistry, Molecular dynamics, nVidia, nVidia GeForce GTX 280, Package, Solvent effects

October 30, 2010 by hgpu

A performance study of general-purpose applications on graphics processors using CUDA

S. Che, M. Boyer, J. Meng, D. Tarjan, J. Sheaffer, K. Skadron

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, OpenMP, Package, Performance

October 30, 2010 by hgpu

GPU-based Video Feature Tracking and Matching

Sudipta N. Sinha, Jan-michael Frahm, Marc Pollefeys, Yakup Genc

View

Download (PDF)

Source codes

Tags: Computer science, Image processing, nVidia, nVidia GeForce 7900 GTX, OpenGL, Package, SIFT

October 29, 2010 by hgpu

The Heisenberg spin glass model on GPU: myths and actual facts

M. Bernaschi, G. Parisi, L. Parisi

View

Download (PDF)

Source codes

Tags: Condensed matter, CUDA, Disordered Systems and Neural Networks, nVidia, nVidia GeForce GTX 480, Package, Physics, Spin Systems, Tesla C1060, Tesla C2050

October 28, 2010 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

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Discrete Wavelet Transform on Consumer-Level Graphics Hardware

Fast and accurate protein substructure searching with simulated annealing and GPUs

Thread-Scalable Evaluation of Multi-Jet Observables

OpenVIDIA: parallel GPU computer vision

High-throughput sequence alignment using Graphics Processing Units

Optimizing data intensive GPGPU computations for DNA sequence alignment

Mars: a MapReduce framework on graphics processors

Exploiting graphics processing units for computational biology and bioinformatics

Accelerating molecular dynamic simulation on graphics processing units

A performance study of general-purpose applications on graphics processors using CUDA

GPU-based Video Feature Tracking and Matching

The Heisenberg spin glass model on GPU: myths and actual facts

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

Most viewed papers (last 30 days)