high performance computing on graphics processing units: hgpu.org

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Computation of Large Covariance Matrices by SAMMY on Graphical Processing Units and Multicore CPUs

G. Arbanas, M.E. Dunn, D. Wiarda

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Tags: CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, Matrix multiplication, Nuclear Experiment, nVidia, Physics, Tesla C2050

December 3, 2011 by hgpu

Efficient Cubic B-spline Image Interpolation on a GPU

Frederic Champagnat, Yves Le Sant

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 260 M, Package, Tesla C2050

December 2, 2011 by hgpu

Massively Parallelized Monte Carlo Simulation and its Applications in Finance

Ashkan Ziabakhshdeylami, Lauren Looi

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Tags: Algorithms, Finance, Monte Carlo simulation, nVidia, Risk Management, Tesla C2050

December 2, 2011 by hgpu

Evaluation of Fermi Features for Data Mining Algorithms

Sinduja Muralidharan

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, Nearest neighbour, nVidia, Tesla C1060, Tesla C2050, Thesis

December 2, 2011 by hgpu

Implementation of the FDTD Method Based on Lorentz-Drude Dispersive Model on GPU for Plasmonics Applications

K.H. Lee, I. Ahmed, R.S.M. Goh, E.H. Khoo, E.P. Li, T.G.G. Hung

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Tags: CUDA, Differential equations, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, Maxwell's equations, nVidia, Tesla C2050

December 2, 2011 by hgpu

A programming language interface to describe transformations and code generation

Gabe Rudy, Malik Murtaza Khan, Mary Hall, Chun Chen, Jacqueline Chame

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Tags: Algorithms, Code generation, Computer science, CUBLAS, CUDA, MPI, nVidia, nVidia GeForce GTX 280, Tesla C2050

December 1, 2011 by hgpu

Iterative optimization methods for efficient image restoration on multicore architectures

Roberto Cavicchioli, Andrea Prearo, Riccardo Zanella, Gaetano Zanghirati, Luca Zanni

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Tags: Algorithms, CUDA, Image processing, MPI, Nonlinear optimization, nVidia, Tesla C2050

December 1, 2011 by hgpu

GPU Computing for Particle Tracking

Hiroshi Nishimura, Kai Song, Krishna Muriki, Changchun Sun, Susan James, Yong Qin

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Tags: CUDA, High Energy Physics - Experiment, nVidia, Physics, Tesla C2050

December 1, 2011 by hgpu

GPGPU Accelerated Cardiac Arrhythmia Simulations

Wei Wang, H. Howie Huang, Matthew Kay, John Cavazos

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Tags: CUDA, Heart, Medicine, nVidia, Tesla C1060, Tesla C2050

November 30, 2011 by hgpu

Unleashing the Power of Distributed CPU/GPU Architectures: Massive Astronomical Data Analysis and Visualization case study

Amr H. Hassan, C. J. Fluke, D. G. Barnes

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Tags: Astrophysics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, nVidia, Tesla C1060, Tesla C2050, Visualization

November 30, 2011 by hgpu

Applications Performance on GPGPUs with the Fermi Architecture

Ahmed Mohamed Hassan Abdalla

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, Performance, Tesla C2050, Tesla M1060, Thesis

November 29, 2011 by hgpu

Dynamic Task Parallelism with a GPU Work-Stealing Runtime System

Sanjay Chatterjee, Max Grossman, Alina Sbirlea, Vivek Sarkar

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Tags: Computer science, CUDA, Data parallelism, nVidia, Task scheduling, Tesla C2050

November 29, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Computation of Large Covariance Matrices by SAMMY on Graphical Processing Units and Multicore CPUs

Efficient Cubic B-spline Image Interpolation on a GPU

Massively Parallelized Monte Carlo Simulation and its Applications in Finance

Evaluation of Fermi Features for Data Mining Algorithms

Implementation of the FDTD Method Based on Lorentz-Drude Dispersive Model on GPU for Plasmonics Applications

A programming language interface to describe transformations and code generation

Iterative optimization methods for efficient image restoration on multicore architectures

GPU Computing for Particle Tracking

GPGPU Accelerated Cardiac Arrhythmia Simulations

Unleashing the Power of Distributed CPU/GPU Architectures: Massive Astronomical Data Analysis and Visualization case study

Applications Performance on GPGPUs with the Fermi Architecture

Dynamic Task Parallelism with a GPU Work-Stealing Runtime System

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

Most viewed papers (last 30 days)