high performance computing on graphics processing units: hgpu.org

Programming

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CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units

Yongchao Liu, Douglas Maskell, Bertil Schmidt

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Smith-Waterman algorithm

November 4, 2010 by hgpu

Fast tridiagonal solvers on the GPU

Yao Zhang, Jonathan Cohen, John D. Owens

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance

November 4, 2010 by hgpu

Benchmarking GPUs to tune dense linear algebra

Vasily Volkov, James W. Demmel

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GTX, nVidia GeForce GTX 280

November 4, 2010 by hgpu

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

Brook for GPUs: Stream Computing on Graphics Hardware

I. Buck, T. Foley, D. Horn, J. Sugerman, K. Mike, H. Pat

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Tags: ATI, ATI Radeon 9800 XT, ATI Stream, Brook, Computer science, High-level Languages, nVidia, nVidia GeForce FX 5900 Ultra, OpenGL, Stream Computing

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

Programming

CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units

Fast tridiagonal solvers on the GPU

Benchmarking GPUs to tune dense linear algebra

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

Brook for GPUs: Stream Computing on Graphics Hardware

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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