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Rapid evaluation and evolution of neural models using graphics card hardware

Thomas F. Clayton, Leena N. Patel, Gareth Leng, Alan F. Murray, Iain A.B. Lindsay

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Evolutionary Computations, nVidia, nVidia GeForce 8800 GTX

January 13, 2011 by hgpu

Speeding up Mutual Information Computation Using NVIDIA CUDA Hardware

Ramtin Shams, Nick Barnes

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

January 13, 2011 by hgpu

Low-cost, high-speed computer vision using NVIDIA’s CUDA architecture

Seung In Park, Sean P. Ponce, Jing Huang, Yong Cao, Francis Quek

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 8800 GTS, Pattern recognition, Video tracking

January 13, 2011 by hgpu

Efficient fault simulation on many-core processors

Michael A. Kochte, Marcel Schaal, Hans-Joachim Wunderlich, Christian G. Zoellin

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Tags: Algorithms, Computer science, CUDA, Fault simulation, nVidia, nVidia GeForce GTX 285

January 13, 2011 by hgpu

K-Means on Commodity GPUs with CUDA

Hong-tao Bai, Li-li He, Dan-tong Ouyang, Zhan-shan Li, Li He

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce 8800 GTX

January 12, 2011 by hgpu

Robust mesh reconstruction from unoriented noisy points

Hoi Sheung, Charlie C. L. Wang

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce 9800 GTX

January 12, 2011 by hgpu

A Variational Model for Interactive Shape Prior Segmentation and Real-Time Tracking

Manuel Werlberger, Thomas Pock, Markus Unger, Horst Bischof

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 280, Video tracking

January 12, 2011 by hgpu

High-Quality Rendering of Varying Isosurfaces with Cubic Trivariate C1-Continuous Splines

Thomas Kalbe, Thomas Koch, Michael Goesele

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Rendering

January 12, 2011 by hgpu

Qilin: exploiting parallelism on heterogeneous multiprocessors with adaptive mapping

Chi-Keung Luk, Sunpyo Hong, Hyesoon Kim

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, Programming techniques

January 12, 2011 by hgpu

Inertial-aided KLT feature tracking for a moving camera

Myung Hwangbo, Jun-Sik Kim, Takeo Kanade

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 Ultra, nVidia GeForce GTX 280, Video tracking

January 12, 2011 by hgpu

Using graphics processing units to generate random numbers

S. Hissoiny, P. Despres, B. Ozell

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Tags: CUDA, nVidia, nVidia GeForce GTX 280, Physics, Pseudo-random number generators

January 12, 2011 by hgpu

Performance potential for simulating spin models on GPU

Martin Weigel

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Source codes

Tags: Computational Physics, CUDA, Disordered Systems and Neural Networks, Heisenberg model, High Energy Physics - Lattice, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Package, Physics, Statistical Mechanics, Tesla C1060

January 12, 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

Programming

Rapid evaluation and evolution of neural models using graphics card hardware

Speeding up Mutual Information Computation Using NVIDIA CUDA Hardware

Low-cost, high-speed computer vision using NVIDIA’s CUDA architecture

Efficient fault simulation on many-core processors

K-Means on Commodity GPUs with CUDA

Robust mesh reconstruction from unoriented noisy points

A Variational Model for Interactive Shape Prior Segmentation and Real-Time Tracking

High-Quality Rendering of Varying Isosurfaces with Cubic Trivariate C1-Continuous Splines

Qilin: exploiting parallelism on heterogeneous multiprocessors with adaptive mapping

Inertial-aided KLT feature tracking for a moving camera

Using graphics processing units to generate random numbers

Performance potential for simulating spin models on 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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