high performance computing on graphics processing units: hgpu.org

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Fast multipole methods on graphics processors

Nail A. Gumerov, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX

November 4, 2010 by hgpu

Solving Dense Linear Systems on Graphics Processors

Sergio Barrachina, Maribel Castillo, Francisco D. Igual, Rafael Mayo, Enrique S. Quintana Ort'?

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

November 4, 2010 by hgpu

Parallel Computing Experiences with CUDA

M. Garland, S. Le Grand, J. Nickolls, J. Anderson, J. Hardwick, S. Morton, E. Phillips, Yao Zhang, V. Volkov

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Tags: Computer science, CUDA, High-level Languages, nVidia

November 4, 2010 by hgpu

GAMER with out-of-core computation

Hsi-Yu Schive, Yu-Chih Tsai, Tzihong Chiueh

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Tesla T10

November 4, 2010 by hgpu

Relational joins on graphics processors

Bingsheng He, Ke Yang, Rui Fang, Mian Lu, Naga Govindaraju, Qiong Luo, Pedro Sander

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Tags: Algorithms, ATI, ATI CAL, ATI R600, ATI Stream, Computer science, CUDA, Join, nVidia, nVidia GeForce 8800 GTX, Sorting

November 4, 2010 by hgpu

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Nathan Bell, Michael Garland

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Package, Sparse matrix

November 4, 2010 by hgpu

CuPP – A framework for easy CUDA integration

Jens Breitbart

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Tags: Computer science, CUDA, High-level Languages, nVidia, Package

November 4, 2010 by hgpu

NBSymple, a double parallel, symplectic N-body code running on Graphic Processing Units

R. Capuzzo-Dolcetta, A. Mastrobuono-Battisti, D. Maschietti

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, OpenMP, Package, Stellar dynamics, Tesla C1060

November 4, 2010 by hgpu

High performance discrete Fourier transforms on graphics processors

Naga K. Govindaraju, Brandon Lloyd, Yuri Dotsenko, Burton Smith, John Manferdelli

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Tags: Computer science, CUDA, FFT, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280

November 3, 2010 by hgpu

Porting a high-order finite-element earthquake modeling application to NVIDIA graphics cards using CUDA

Dimitri Komatitsch, David Michea, Gordon Erlebacher

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Tags: CUDA, Finite element method, Geoscience, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Spectral methods

November 3, 2010 by hgpu

Harvesting graphics power for MD simulations

J. A. van Meel, A. Arnold, D. Frenkel, Portegies S. F. Zwart, R. G. Belleman

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Tags: Condensed matter, CUDA, Molecular dynamics, nVidia, nVidia GeForce 8800 GTX, Soft Condensed Matter

November 3, 2010 by hgpu

Real-time Visual Tracker by Stream Processing

Oscar Mateo Lozano, Kazuhiro Otsuka

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Tags: CMP, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Particle filtering, Video tracking

November 3, 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

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high performance computing on graphics processing units: hgpu.org

Fast multipole methods on graphics processors

Solving Dense Linear Systems on Graphics Processors

Parallel Computing Experiences with CUDA

GAMER with out-of-core computation

Relational joins on graphics processors

Implementing sparse matrix-vector multiplication on throughput-oriented processors

CuPP – A framework for easy CUDA integration

NBSymple, a double parallel, symplectic N-body code running on Graphic Processing Units

High performance discrete Fourier transforms on graphics processors

Porting a high-order finite-element earthquake modeling application to NVIDIA graphics cards using CUDA

Harvesting graphics power for MD simulations

Real-time Visual Tracker by Stream Processing

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

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