high performance computing on graphics processing units: hgpu.org

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Load Balancing in Data Warehouse – Evolution and Perspectives

Michal Gorawski

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Tags: Algorithms, Cloud, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260

October 6, 2014 by hgpu

Embedding GPU Computations in Hadoop

Jie Zhu, Hai Jiang, Juanjuan Li, Erikson Hardesty, Kuan-Ching Li, Zhongwen Li

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Tags: Cloud, Computer science, CUDA, Hadoop, Heterogeneous systems, Java, MapReduce, nVidia, nVidia GeForce GTX 480, Task scheduling

October 6, 2014 by hgpu

Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

Di Wu, Ling Shao

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Tags: CNN, Computer science, CUDA, Neural networks, nVidia, Package, Python, Rendering

October 4, 2014 by hgpu

GPU Accelerated Radio Wave Propagation Modeling Using Ray Tracing

Alaettin Zubaroglu

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Tags: CUDA, nVidia, Raytracing, Signal processing, Tesla C2075, Tesla K20, Thesis

October 4, 2014 by hgpu

Parallel Shortest Path Algorithm for Voronoi Diagrams with Generalized Distance Functions

Julio Toss, Joao Comba, Bruno Raffin

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Voronoi diagram

October 4, 2014 by hgpu

Teaching Parallel Programming Using Java

Aamir Shafi, Aleem Akhtar, Ansar Javed, Bryan Carpenter

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Tags: Computer science, CUDA, Education, Hadoop, Java, MapReduce, MPI, nVidia, Programming techniques, Software Engineering

October 4, 2014 by hgpu

A massively parallel algorithm for constructing the BWT of large string sets

Jacopo Pantaleoni

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Tags: Algorithms, Bioinformatics, Computer science, CUDA, nVidia, Tesla K40

October 4, 2014 by hgpu

Fast Automatic Heuristic Construction Using Active Learning

William F. Ogilvie, Pavlos Petoumenos, Zheng Wang, Hugh Leather

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX Titan

October 3, 2014 by hgpu

Microarchitectural Performance Characterization of Irregular GPU Kernels

Molly A. O'Neil, Martin Burtscher

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Performance

October 3, 2014 by hgpu

Stable large-scale solver for Ginzburg-Landau equations for superconductors

I. A. Sadovskyy, A. E. Koshelev, C. L. Phillips, D. A. Karpeev, A. Glatz

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Tags: Algorithms, Condensed matter, CUDA, Numerical simulation, nVidia, Tesla K20

October 3, 2014 by hgpu

A fast GPU-based Monte Carlo simulation of proton transport with detailed modeling of non-elastic interactions

H. Wan Chan Tseung, J. Ma, C. Beltran

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Tags: CUDA, Medical Physics, Monte Carlo simulation, nVidia, nVidia GeForce GTX 680, Physics, Tesla K20

October 3, 2014 by hgpu

A stencil-based implementation of Parareal in the C++ domain specific embedded language STELLA

Andrea Arteaga, Daniel Ruprecht, Rolf Krause

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Tags: Computer science, CUDA, Differential equations, MPI, nVidia, Partial differential equations, PDEs, Tesla K20

October 3, 2014 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

GPU Accelerated Radio Wave Propagation Modeling Using Ray Tracing

Parallel Shortest Path Algorithm for Voronoi Diagrams with Generalized Distance Functions

Teaching Parallel Programming Using Java

A massively parallel algorithm for constructing the BWT of large string sets

Fast Automatic Heuristic Construction Using Active Learning

Microarchitectural Performance Characterization of Irregular GPU Kernels

Stable large-scale solver for Ginzburg-Landau equations for superconductors

A fast GPU-based Monte Carlo simulation of proton transport with detailed modeling of non-elastic interactions

A stencil-based implementation of Parareal in the C++ domain specific embedded language STELLA

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Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

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