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Simple Geometry Compression for Ray Tracing on GPU

Kirill Garanzha, Alexander Bely, Vladimir Galaktionov

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing

December 26, 2011 by hgpu

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

Lu Zheng, Ole J. Mengshoel, Jike Chong

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Tags: Algorithms, Bayesian, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 460

December 26, 2011 by hgpu

SSLShader: Cheap SSL Acceleration with Commodity Processors

Keon Jang, Sangjin Han, Seungyeop Han, Sue Moon, KyoungSoo Park

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Tags: AES, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Security

December 26, 2011 by hgpu

Accurate Sequence Alignment using Distributed Filtering on GPU Clusters

Reza Farivar, Shivaram Venkataraman, Yanen Li, Ellick Chan, Abhishek Verma, Roy H. Campbell

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Tags: Bioinformatics, Biology, CUDA, Filtering, GPU cluster, nVidia, Sequence alignment, Tesla S1070

December 26, 2011 by hgpu

Multifrontal Factorization of Sparse SPD Matrices on GPUs

Thomas George, Vaibhav Saxena, Anshul Gupta, Amik Singh, Anamitra R. Choudhury

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Tags: Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla S1070

December 26, 2011 by hgpu

A Novel GPU-Based Deformation Pipeline

Muhammad Mobeen Movania, Lin Feng

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, OpenGL, Rendering

December 26, 2011 by hgpu

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Qi Li

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Optimization, Sorting, Tesla C1060, Tesla C2050, Tesla C2070, Thesis

December 26, 2011 by hgpu

Designing Fast Architecture Sensitive Tree Search on Modern Multi-Core/Many-Core Processors

Changkyu Kim, Jatin Chhugani, Nadathur Satish, Eric Sedlar, Anthony D. Nguyen, Tim Kaldewey, Victor W. Lee, Scott A. Brandt, Pradeep Dubey

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Tags: Compression, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 280, Search, Tesla C2050

December 25, 2011 by hgpu

Turbo Bayesian Compressed Sensing

Depeng Yang

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Tags: Algorithms, Bayesian, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 480, Sensing, Signal processing

December 25, 2011 by hgpu

Modeling Parallel Programs for Heterogeneous Computing

Ferosh Jacob

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance

December 25, 2011 by hgpu

Methodology of control and supervision of web connected mobile robots with CUDA technology application

Janusz Bedkowski, Andrzej Maslowski

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, nVidia Quadro FX 1600 M, nVidia Quadro FX 3700

December 25, 2011 by hgpu

Accelerating linear system solutions using randomization techniques

Marc Baboulin, Jack Dongarra, Julien Herrmann, Stanimire Tomov

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla C2050

December 25, 2011 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Simple Geometry Compression for Ray Tracing on GPU

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

SSLShader: Cheap SSL Acceleration with Commodity Processors

Accurate Sequence Alignment using Distributed Filtering on GPU Clusters

Multifrontal Factorization of Sparse SPD Matrices on GPUs

A Novel GPU-Based Deformation Pipeline

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Designing Fast Architecture Sensitive Tree Search on Modern Multi-Core/Many-Core Processors

Turbo Bayesian Compressed Sensing

Modeling Parallel Programs for Heterogeneous Computing

Methodology of control and supervision of web connected mobile robots with CUDA technology application

Accelerating linear system solutions using randomization techniques

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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