high performance computing on graphics processing units: hgpu.org

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High performance implementation of hydrodynamic interactions and applications with the sub-cellular element method

Andrei Frunza

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Tags: Computer science, CUDA, Diffusion tensor, nVidia, nVidia GeForce GTX 580, Physics, Thesis

June 21, 2012 by hgpu

Evaluating the impact of reordering unstructured meshes on the performance of finite volume GPU solvers

Marc de la Asuncion, Jose M. Mantas, Manuel J. Castro

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Tags: Computer science, CUDA, Finite volume method, nVidia, nVidia GeForce GTX 580, Performance

June 21, 2012 by hgpu

Parallel Rendering on Hybrid Multi-GPU Clusters

S. Eilemann, A. Bilgili, M. Abdellah, J. Hernando, M. Makhinya, R. Pajarola, F. Schurmann

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Tags: 3D Graphics and Realism, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 580, OpenGL, Optimization, Rendering, Visualization

June 19, 2012 by hgpu

Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation

Holger Schwenk, Anthony Rousseau, Mohammed Attik

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Source codes

Tags: Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package, Speech recognition, Tesla M2090

June 11, 2012 by hgpu

Sparse LU Factorization for Parallel Circuit Simulation on GPU

Ling Ren, Xiaoming Chen, Yu Wang, Chenxi Zhang, Huazhong Yang

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Tags: ATI, ATI Radeon HD 5870, CAD, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

June 9, 2012 by hgpu

A Compiler and Runtime for Heterogeneous Computing

Joshua Auerbach, David F. Bacon, Ioana Burcea, Perry Cheng, Stephen J. Fink, Rodric Rabbah, Sunil Shukla

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Tags: Computer science, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 580, OpenCL, Programming Languages

June 4, 2012 by hgpu

GPU Join Processing Revisited

Tim Kaldewey, Guy Lohman, Rene Mueller, Peter Volk

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 580

June 3, 2012 by hgpu

Towards Distributed Heterogenous High-Performance Computing with ViennaCL

Josef Weinbub, Karl Rupp, Siegfried Selberherr

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Tags: Benchmarking, Computer science, Distributed computing, MPI, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 580, OpenCL, Package, Tesla C2050

June 1, 2012 by hgpu

Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born

Andreas W. Gotz, Mark J. Williamson, Dong Xu, Duncan Poole, Scott Le Grand, Ross C. Walker

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Tags: Algorithms, Chemistry, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 580, Tesla C1060, Tesla C2070, Tesla M2090

May 26, 2012 by hgpu

Computing 2D Alpha Shapes Using GPU

Srinivasan Kidambi Sridharan, Ashwin Nanjappa

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package

May 20, 2012 by hgpu

A GPU Algorithm for 3D Convex Hull

Mingcen Gao, Thanh-Tung Cao, Ashwin Nanjappa, Tiow-Seng Tan, Zhiyong Huang

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580

May 19, 2012 by hgpu

Accelerated GPU Simulation of Compressible Flow by the Discontinuous Evolution Galerkin Method

Block B. J., Lukacova-Medvid'ova M., Virnau P., Yelash L.

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Tags: CUDA, Fluid dynamics, Numerical simulation, nVidia, nVidia GeForce GTX 580

May 19, 2012 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

High performance implementation of hydrodynamic interactions and applications with the sub-cellular element method

Evaluating the impact of reordering unstructured meshes on the performance of finite volume GPU solvers

Parallel Rendering on Hybrid Multi-GPU Clusters

Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation

Sparse LU Factorization for Parallel Circuit Simulation on GPU

A Compiler and Runtime for Heterogeneous Computing

GPU Join Processing Revisited

Towards Distributed Heterogenous High-Performance Computing with ViennaCL

Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born

Computing 2D Alpha Shapes Using GPU

A GPU Algorithm for 3D Convex Hull

Accelerated GPU Simulation of Compressible Flow by the Discontinuous Evolution Galerkin Method

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)