high performance computing on graphics processing units: hgpu.org

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Inter-Block GPU Communication via Fast Barrier Synchronization

Shucai Xiao, Wu-chun Feng

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

March 5, 2011 by hgpu

Towards a Software Transactional Memory for Graphics Processors

Daniel Cederman, Philippas Tsigas and Muhammad Tayyab Chaudhry

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, Programming techniques

March 4, 2011 by hgpu

Smooth Mixed-Resolution GPU Volume Rendering

Johanna Beyer, Markus Hadwiger, Torsten Moller, Laura Fritz

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 280, OpenGL, Rendering, Visualization

March 3, 2011 by hgpu

Singular value decomposition for collaborative filtering on a GPU

Kimikazu Kato, Tikara Hosino

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Tags: Computer science, CUDA, Data Structures and Algorithms, Filtering, nVidia, nVidia GeForce GTX 280

March 3, 2011 by hgpu

Performance and accuracy of hardware-oriented native-, emulated- and mixed-precision solvers in FEM simulations (Part 2: Double Precision GPUs)

Dominik Goddeke and Robert Strzodka

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Tags: Computer science, Conjugate gradient solver, CUDA, Extended precision, Mixed precision, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Partial differential equations, PDEs, Sparse linear iterative solvers

March 2, 2011 by hgpu

Mixed-Precision GPU-Multigrid Solvers with Strong Smoothers

Dominik Goddeke, Robert Strzodka

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Tags: CUDA, Mathematics, Mixed precision, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs

March 2, 2011 by hgpu

Hardware-Oriented Multigrid Finite Element Solvers on GPU-Accelerated Clusters

Stefan Turek, Dominik Goddeke, Sven H.M. Buijssen, Hilmar Wobker

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Tags: CUDA, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 280, Package

March 2, 2011 by hgpu

FEAST – Realisation of hardware-oriented Numerics for HPC simulations with Finite Elements

Stefan Turek, Dominik Goddeke, Christian Becker, Sven H.M. Buijssen, Hilmar Wobker

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Tags: CUDA, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 280, Package

March 1, 2011 by hgpu

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Edans Flavius O. Sandes, Alba Cristina M.A. de Melo

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, Sequence alignment, Smith-Waterman algorithm

February 27, 2011 by hgpu

An efficient GPU-based approach for interactive global illumination

Rui Wang, Rui Wang, Kun Zhou, Minghao Pan, Hujun Bao

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Tags: 3D Graphics and Realism, Computer science, KD-tree, nVidia, nVidia GeForce GTX 280, Rendering

February 24, 2011 by hgpu

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

Kanupriya Gulati and Sunil P Khatri

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280

February 21, 2011 by hgpu

Assembling large mosaics of electron microscope images using GPU

Kannan Umadevi Venkataraju, Mark Kim, Dan Gerszewski, James R. Anderson, Mary Hall

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Tags: CUDA, Electron microscopy, Image processing, nVidia, nVidia GeForce GTX 280

February 21, 2011 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

Inter-Block GPU Communication via Fast Barrier Synchronization

Towards a Software Transactional Memory for Graphics Processors

Smooth Mixed-Resolution GPU Volume Rendering

Singular value decomposition for collaborative filtering on a GPU

Performance and accuracy of hardware-oriented native-, emulated- and mixed-precision solvers in FEM simulations (Part 2: Double Precision GPUs)

Mixed-Precision GPU-Multigrid Solvers with Strong Smoothers

Hardware-Oriented Multigrid Finite Element Solvers on GPU-Accelerated Clusters

FEAST – Realisation of hardware-oriented Numerics for HPC simulations with Finite Elements

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

An efficient GPU-based approach for interactive global illumination

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

Assembling large mosaics of electron microscope images using GPU

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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