high performance computing on graphics processing units: hgpu.org

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Parallel Implementation of Finite Element Codes using CUDA

Shi-Lun Huang

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Tags: Computer science, Conjugate gradient solver, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560

June 6, 2013 by hgpu

Facial Recognition Using Neural Networks over GPGPU

Juan Pablo Balarini, Sergio Nesmachnow, Martin Rodriguez

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 480

November 18, 2012 by hgpu

An Optimized Parallel IDCT on Graphics Processing Units

Biao Wang, Mauricio Alvarez-Mesa, Chi Ching Chi, Ben Juurlink

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Tags: Computer science, H.264/AVC, nVidia, nVidia GeForce GT 430, nVidia GeForce GTS 450, nVidia GeForce GTX 560 Ti, OpenCL

September 14, 2012 by hgpu

GPU-Assisted Cryptography of Log-Structured Indices

Michael Warren Kirby

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Tags: Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce 9400 M, nVidia GeForce GTS 450, nVidia GeForce GTX 480 M, nVidia GeForce GTX 550 Ti, Security, Thesis

August 15, 2012 by hgpu

Real-Time Exact Graph Matching with Application in Human Action Recognition

Oya Celiktutan, Christian Wolf, Bulent Sankur, Eric Lombardi

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560, Pattern recognition

August 13, 2012 by hgpu

Heterogeneous Computing in Economics: a Simplified Approach

Matt P. Dziubinski, Stefano Grassi

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Tags: CUDA, Data parallelism, Finance, Heterogeneous systems, nVidia, nVidia GeForce GT 520 M, nVidia GeForce GTS 450, Optimization

May 14, 2012 by hgpu

The AGILE library for image reconstruction in biomedical sciences using graphics card hardware acceleration

Manuel Freiberger, Florian Knoll, Kristian Bredies, Hermann Scharfetter, Rudolf Stollberger

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Tags: Algorithms, CUDA, Image processing, Image reconstruction, Magnetic resonance imaging, Medicine, MRI, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 480, Package, Tomography

April 28, 2012 by hgpu

Exploiting Segmentation for Robust 3D Object Matching

Michael Krainin, Kurt Konolige, Dieter Fox

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTS 450, OpenGL, Package

February 18, 2012 by hgpu

Fast Polynomial Approximation Acceleration on the GPU

Lumir Janosek, Martin Nemec

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9600 GT, nVidia GeForce 9800 GTX, nVidia GeForce GTS 450

February 12, 2012 by hgpu

Scalable Multi-Cache Simulation Using GPUs

Michael Moeng, Sangyeun Cho, Rami Melhem

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Tags: Analytical model, Computer science, CUDA, FPGA, Memory, nVidia, nVidia GeForce GTS 450

November 27, 2011 by hgpu

Efficient GPGPU-based parallel packet classification

Che-Lun Hung, Yaw-Ling Lin, Kuan-Ching Li, Hsiao-Hsi Wang, Shih-Wei Guo

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Tags: Algorithms, Computer science, CUDA, Filtering, Network communications, nVidia, nVidia GeForce GTS 450, Security

November 21, 2011 by hgpu

Variable selection in a GPU cluster using delta test

A. Guillen, M. van Heeswijk, D. Sovilj, M. G. Arenas, L. J. Herrera, H. Pomares, I. Rojas

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Tags: Algorithms, Computer science, Genetic programming, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GTX, nVidia GeForce GTS 450, Optimization

November 15, 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

Parallel Implementation of Finite Element Codes using CUDA

Facial Recognition Using Neural Networks over GPGPU

An Optimized Parallel IDCT on Graphics Processing Units

GPU-Assisted Cryptography of Log-Structured Indices

Real-Time Exact Graph Matching with Application in Human Action Recognition

Heterogeneous Computing in Economics: a Simplified Approach

The AGILE library for image reconstruction in biomedical sciences using graphics card hardware acceleration

Exploiting Segmentation for Robust 3D Object Matching

Fast Polynomial Approximation Acceleration on the GPU

Scalable Multi-Cache Simulation Using GPUs

Efficient GPGPU-based parallel packet classification

Variable selection in a GPU cluster using delta test

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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