high performance computing on graphics processing units: hgpu.org

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GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation

Xun Jia, Yifei Lou, John Lewis, Ruijiang Li, Xuejun Gu, Chunhua Men, William Y. Song, Steve B. Jiang

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Tags: Computed tomography, CT, CUDA, Image reconstruction, Medical Physics, nVidia, Physics, Tesla C1060

November 13, 2010 by hgpu

Tiling for Performance Tuning on Different Models of GPUs

Chang Xu, Steven R. Kirk, Samantha Jenkins

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 260, Performance

November 13, 2010 by hgpu

Advanced Architectures for Astrophysical Supercomputing

Benjamin R. Barsdell, David G. Barnes, Christopher J. Fluke

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia

November 12, 2010 by hgpu

RapidMind: Portability across Architectures and its Limitations

Iris Christadler, Volker Weinberg

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Tags: Cell processor, Computer science, CUDA, nVidia, Performance, Programming Languages, Tesla C1060, Tesla S1070

November 12, 2010 by hgpu

GPU-Based Volume Rendering of Noisy Multi-Spectral Astronomical Data

Amr H. Hassan, Christopher J. Fluke, David G. Barnes

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, MPI, nVidia

November 12, 2010 by hgpu

Real-time digital holographic microscopy observable in multi-view and multi-resolution

Tomoyoshi Shimobaba, Nobuyuki Masuda, Yasuyuki Ichihashi, Tomoyoshi Ito

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Source codes

Tags: Biological Physics, Computational Physics, Computer holography, CUDA, nVidia, nVidia GeForce GTX 295, Optics, Package, Physics

November 12, 2010 by hgpu

GPU-based Fast Cone Beam CT Reconstruction from Undersampled and Noisy Projection Data via Total Variation

Xun Jia, Yifei Lou, Ruijiang Li, William Y. Song, Steve B. Jiang

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Tags: CT, CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Tesla C1060

November 12, 2010 by hgpu

Exploring the Limits of GPUs With Parallel Graph Algorithms

Frank Dehne, Kumanan Yogaratnam

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 260, Performance

November 12, 2010 by hgpu

Langevin dynamics simulations of biomolecules on graphics processors

A. Zhmurov, R. I. Dima, Y. Kholodov, V. Barsegov

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Tags: Biological Physics, Biomolecules, Condensed matter, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 295, Physics, Soft Condensed Matter

November 12, 2010 by hgpu

GPGPU based simulations for one and two dimensional quantum walks

Marek Sawerwain, Roman Gielerak

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Tags: Computational Physics, CUDA, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 280, Physics, Quantum walks

November 12, 2010 by hgpu

Enabling a High Throughput Real Time Data Pipeline for a Large Radio Telescope Array with GPUs

R. G. Edgar, M. A. Clark, K. Dale, D. A. Mitchell, S. M. Ord, R. B. Wayth, H. Pfister, L. J. Greenhill

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Tags: Astrophysics, Computational Physics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Tesla C1060

November 12, 2010 by hgpu

GPU-based ultra-fast direct aperture optimization for online adaptive radiation therapy

Chunhua Men, Xun Jia, Steve. B. Jiang

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Tags: CUDA, Medical Physics, Medicine, nVidia, nVidia GeForce 9500 GT, nVidia GeForce GTX 285, Physics, Radiotherapy, Tesla C1060

November 12, 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

GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation

Tiling for Performance Tuning on Different Models of GPUs

Advanced Architectures for Astrophysical Supercomputing

RapidMind: Portability across Architectures and its Limitations

GPU-Based Volume Rendering of Noisy Multi-Spectral Astronomical Data

Real-time digital holographic microscopy observable in multi-view and multi-resolution

GPU-based Fast Cone Beam CT Reconstruction from Undersampled and Noisy Projection Data via Total Variation

Exploring the Limits of GPUs With Parallel Graph Algorithms

Langevin dynamics simulations of biomolecules on graphics processors

GPGPU based simulations for one and two dimensional quantum walks

Enabling a High Throughput Real Time Data Pipeline for a Large Radio Telescope Array with GPUs

GPU-based ultra-fast direct aperture optimization for online adaptive radiation therapy

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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