high performance computing on graphics processing units: hgpu.org

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High-Performance Iterative Electron Tomography Reconstruction with Long-Object Compensation using Graphics Processing Units (GPUs)

Wei Xu, Fang Xu, Mel Jones, Bettina Keszthelyi, John Sedat, David Agard, Klaus Mueller

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Tags: Computed tomography, CT, CUDA, GLSL, Image processing, Image reconstruction, Medicine, nVidia, nVidia GeForce 7800 GTX, nVidia GeForce GTX 280, Tomography

November 19, 2010 by hgpu

Rodinia: A benchmark suite for heterogeneous computing

Shuai Che, Michael Boyer, Jiayuan Meng, David Tarjan, Jeremy W. Sheaffer, Sang-Ha Lee, Kevin Skadron

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenMP

November 19, 2010 by hgpu

Multi-dimensional characterization of temporal data mining on graphics processors

J. Archuleta, Yong Cao, T. Scogland, Wu-Chun Feng

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Tags: Computer science, CUDA, Data mining, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280

November 19, 2010 by hgpu

A GPGPU compiler for memory optimization and parallelism management

Yi Yang, Ping Xiang, Jingfei Kong, Huiyang Zhou

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Tags: Computer science, CUBLAS, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Package

November 18, 2010 by hgpu

FAST: fast architecture sensitive tree search on modern CPUs and GPUs

Changkyu Kim, Jatin Chhugani, Nadathur Satish, Eric Sedlar, Anthony D. Nguyen, Tim Kaldewey, Victor W. Lee, Scott A. Brandt, Pradeep Dubey

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

November 17, 2010 by hgpu

permGPU: Using graphics processing units in RNA microarray association studies

Ivo Shterev, Sin H. Jung, Stephen George, Kouros Owzar

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 280, Package, RNA

November 17, 2010 by hgpu

Accelerating the reduction to upper Hessenberg, tridiagonal, and bidiagonal forms through hybrid GPU-based computing

Stanimire Tomov, Rajib Nath, Jack Dongarra

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Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Package

November 17, 2010 by hgpu

A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

Jayram Moorkanikara M. Nageswaran, Nikil Dutt, Jeffrey L. Krichmar, Alex Nicolau, Alexander V. Veidenbaum

Tags: Biology, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, STDP

November 13, 2010 by hgpu

Time dependent simulation of the Driven Lid Cavity at High Reynolds Number

N. Cardoso, P. Bicudo

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Tags: CUDA, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 280

November 13, 2010 by hgpu

Fast GPU Implementation of Sparse Signal Recovery from Random Projections

M. Andrecut

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Tags: CUDA, nVidia, nVidia GeForce 8400 GS, nVidia GeForce GTX 280, Signal processing

November 13, 2010 by hgpu

Parallel Algorithm for Solving Kepler’s Equation on Graphics Processing Units: Application to Analysis of Doppler Exoplanet Searches

Eric B. Ford

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Tags: Astrophysics, CUDA, Earth and Planetary Astrophysics, Gravitation, nVidia, nVidia GeForce GTX 280

November 13, 2010 by hgpu

Parallel GPU Implementation of Iterative PCA Algorithms

M. Andrecut

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Tags: Algorithms, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

November 13, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

High-Performance Iterative Electron Tomography Reconstruction with Long-Object Compensation using Graphics Processing Units (GPUs)

Rodinia: A benchmark suite for heterogeneous computing

Multi-dimensional characterization of temporal data mining on graphics processors

A GPGPU compiler for memory optimization and parallelism management

FAST: fast architecture sensitive tree search on modern CPUs and GPUs

permGPU: Using graphics processing units in RNA microarray association studies

Accelerating the reduction to upper Hessenberg, tridiagonal, and bidiagonal forms through hybrid GPU-based computing

A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

Time dependent simulation of the Driven Lid Cavity at High Reynolds Number

Fast GPU Implementation of Sparse Signal Recovery from Random Projections

Parallel Algorithm for Solving Kepler’s Equation on Graphics Processing Units: Application to Analysis of Doppler Exoplanet Searches

Parallel GPU Implementation of Iterative PCA Algorithms

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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