high performance computing on graphics processing units: hgpu.org

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Efficient Knowledge Extraction from Structured Data

Bianca Wackersreuther

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Tags: Algorithms, Clustering, Compression, Computer science, CUDA, Data mining, Databases, Heterogeneous systems, Hierarchical clustering, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Thesis

January 14, 2012 by hgpu

GPU-based parallel solver via the Kantorovich theorem for the nonlinear Bernstein polynomial systems

Feifei Wei, Jieqing Feng, Hongwei Lin

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Tags: Algorithms, CUDA, Mathematics, Nonlinear Sciences, nVidia, nVidia GeForce GTX 280

January 13, 2012 by hgpu

Implementing Genetic Algorithms to CUDA Environment Using Data Parallelization

Masashi Oiso, Yoshiyuki Matsumura, Toshiyuki Yasuda, Kazuhiro Ohkura

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 280

January 11, 2012 by hgpu

Power-performance comparison of single-task driven many-cores

Fuat Keceli, Tali Moreshet, Uzi Vishkin

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 280

January 11, 2012 by hgpu

Providing Source Code Level Portability Between CPU and GPU with MapCG

Chun-Tao Hong, De-Hao Chen, Yu-Bei Chen, Wen-Guang Chen, Wei-Min Zheng, Hai-Bo Lin

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Tags: Code generation, Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL

January 9, 2012 by hgpu

High Performance and Scalable GPU Graph Traversal

Duane Merrill, Michael Garland, Andrew Grimshaw

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 280, Tesla C2050

January 9, 2012 by hgpu

Artifact-Free JPEG Decompression with Total Generalized Variation

Kristian Bredies, Martin Holler

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, nVidia Quadro FX 3700

January 6, 2012 by hgpu

Low-power Task Scheduling for GPU Energy Reduction

Li Tang, Yiji Zhang

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 210, nVidia GeForce GTX 280, nVidia GeForce GTX 570, Operating systems, Task scheduling

January 6, 2012 by hgpu

Architecture-Aware Mapping and Optimization on a 1600-Core GPU

Mayank Daga, Thomas Scogland, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Performance

January 3, 2012 by hgpu

GPU Computing for Parallel Local Search Metaheuristics

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Optimization, Tesla M2050

January 3, 2012 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

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

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Efficient Knowledge Extraction from Structured Data

GPU-based parallel solver via the Kantorovich theorem for the nonlinear Bernstein polynomial systems

Implementing Genetic Algorithms to CUDA Environment Using Data Parallelization

Power-performance comparison of single-task driven many-cores

Providing Source Code Level Portability Between CPU and GPU with MapCG

High Performance and Scalable GPU Graph Traversal

Artifact-Free JPEG Decompression with Total Generalized Variation

Low-power Task Scheduling for GPU Energy Reduction

Architecture-Aware Mapping and Optimization on a 1600-Core GPU

GPU Computing for Parallel Local Search Metaheuristics

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

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

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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