high performance computing on graphics processing units: hgpu.org

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High performance direct gravitational N-body simulations on graphics processing units II: An implementation in CUDA

Robert G. Belleman, Jeroen Bedorf, Simon F. Portegies Zwart

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Tags: Astrophysics, CUDA, Gravitation, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Stellar dynamics

October 30, 2010 by hgpu

Ultrasound goes GPU: real-time simulation using CUDA

Tobias Reichl, Josh Passenger, Oscar Acosta, Olivier Salvado

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Tags: CUDA, Image-guided therapy, Medicine, nVidia, nVidia GeForce 8800 GTX, Surgical simulation, Ultrasound, Visualization

October 29, 2010 by hgpu

An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Computer science, CUDA, Memory level parallelism, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTX, nVidia Quadro FX 5600, Warp level parallelism

October 29, 2010 by hgpu

GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration

G. C. Sharp, N. Kandasamy, H. Singh, M. Folkert

Tags: Brook, Computed radiography, Computer science, Image processing, Medicine, nVidia, nVidia GeForce 8800 GTX

October 28, 2010 by hgpu

CUDA cuts: Fast graph cuts on the GPU

Vibhav Vineet, P. J. Narayanan

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX

October 28, 2010 by hgpu

An adaptive performance modeling tool for GPU architectures

Sara S. Baghsorkhi, Matthieu Delahaye, Sanjay J. Patel, William D. Gropp, Wen mei

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Tags: Analytical model, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Performance

October 28, 2010 by hgpu

Accelerating astrophysical particle simulations with programmable hardware (FPGA and GPU)

R. Spurzem, P. Berczik, G. Marcus, A. Kugel, G. Lienhart, I. Berentzen, R. Manner, R. Klessen, R. Banerjee

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Tags: Astrophysics, FPGA, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Particle simulation, Special purpose accelerators

October 28, 2010 by hgpu

CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment

Svetlin Manavski, Giorgio Valle

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Source codes

Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Sequence alignment, Smith-Waterman algorithm

October 28, 2010 by hgpu

GPU-Based Monte-Carlo Volume Raycasting

C. R. Salama

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 8800 GTX, OpenGL, Raytracing, Rendering

October 28, 2010 by hgpu

Accelerating Large Graph Algorithms on the GPU Using CUDA

Pawan Harish, P. Narayanan

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce 8800 GTX

October 28, 2010 by hgpu

Stochastic DT-MRI Connectivity Mapping on the GPU

Tim McGraw, Mariappan Nadar

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Tags: Computer science, Diffusion tensor, GLSL, Magnetic resonance imaging, nVidia, nVidia GeForce 8800 GTX, OpenGL, Stochastic tractography

October 28, 2010 by hgpu

GPU-accelerated large-scale quantum molecular dynamics simulation of 3-dimensional C60 polymers

Toshiaki Iitaka

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Tags: Computational Physics, CUDA, Materials Science, Molecular dynamics, nVidia, nVidia GeForce 8800 GTX, Physics

October 28, 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 direct gravitational N-body simulations on graphics processing units II: An implementation in CUDA

Ultrasound goes GPU: real-time simulation using CUDA

An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness

GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration

CUDA cuts: Fast graph cuts on the GPU

An adaptive performance modeling tool for GPU architectures

Accelerating astrophysical particle simulations with programmable hardware (FPGA and GPU)

CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment

GPU-Based Monte-Carlo Volume Raycasting

Accelerating Large Graph Algorithms on the GPU Using CUDA

Stochastic DT-MRI Connectivity Mapping on the GPU

GPU-accelerated large-scale quantum molecular dynamics simulation of 3-dimensional C60 polymers

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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