high performance computing on graphics processing units: hgpu.org

Jeffrey S. Vetter, Richard Glassbrook, Jack Dongarra, Karsten Schwan, Bruce Loftis, Stephen McNally, Jeremy Meredith, James Rogers, Philip Roth Kyle Spafford, Sudhakar Yalamanchili

View

Download (PDF)

Tags: Computer science, Hardware Architecture, Heterogeneous systems, nVidia, Tesla M2070

November 7, 2011 by hgpu

Accelerating Large Scale Image Analyses on Parallel CPU-GPU Equipped Systems

George Teodoro, Tahsin M. Kurc, Tony Pan, Lee Cooper, Jun Kong, Patrick Widener, Joel H. Saltz

View

Download (PDF)

Tags: CUDA, Heterogeneous systems, Image processing, nVidia, Tesla M2070

October 14, 2011 by hgpu

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

Zane W. Bell, Greg G. Davidson, Ed D'Azevedo, Thomas M. Evans, Wayne Joubert, John K. Munro, Jr., Dilip R. Patlolla, Bogdan Vacaliuc

View

Download (PDF)

Source codes

Tags: Boltzmann equation, CUDA, Heterogeneous systems, nVidia, Package, Physics, Presentation, Python, Tesla M2070

October 6, 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

* * *

high performance computing on graphics processing units: hgpu.org

VOCL: An Optimized Environment for Transparent Virtualization of Graphics Processing Units

Implementing Molecular Dynamics on Hybrid High Performance Computers – Particle-Particle Particle-Mesh

Graduate Operating Systems: Project Report

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

Soft Error Resilient QR Factorization for Hybrid System with GPGPU

Soft Error Resilient QR Factorization for Hybrid System

Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures

Prospects for scalable 3D FFTs on heterogeneous exascale systems

A Class of Hybrid LAPACK Algorithms for Multicore and GPU Architectures

Keeneland: Bringing heterogeneous GPU computing to the computational science community

Accelerating Large Scale Image Analyses on Parallel CPU-GPU Equipped Systems

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

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)