high performance computing on graphics processing units: hgpu.org

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Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Christoph Kessler, Usman Dastgeer, Lu Li

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Review, Tesla C2050

May 15, 2014 by hgpu

Build and Travel KD-Tree with CUDA

Meng Zhou

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Tags: 3D Graphics and Realism, Computer science, CUDA, KD-tree, nVidia, nVidia GeForce GTX 780 Ti, Package, Raytracing

May 14, 2014 by hgpu

Efficient Energyminimization in Finite-Difference Micromagnetics: Speeding up Hysteresis Computations

Claas Abert, Gregor Wautischer, Florian Bruckner, Armin Satz, Dieter Suess

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Tags: Computational Physics, CUDA, Electrodynamics, Finite difference, nVidia, Package, Physics, Python

May 14, 2014 by hgpu

Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink

Patrick Charrier, Mariusz Klimek, Christian Steinmetz, Dietmar Hildenbrand

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, OpenCL, Package

May 12, 2014 by hgpu

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

Shuang Wang, Jihoon Kim, Xiaoqian Jiang, Stefan F Brunner, Lucila Ohno-Machado

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, RNA, Smith-Waterman algorithm, Tesla M2090

May 10, 2014 by hgpu

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

Brice Goglin

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Package, Xeon Phi

May 7, 2014 by hgpu

Improving the Programmability of GPU Architectures

Cedric Nugteren

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenACC, OpenCL, Package, Performance, Thesis

May 7, 2014 by hgpu

Non-separable 2D, 3D and 4D filtering with CUDA

Anders Eklund, Paul Dufort

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Tags: CUDA, FFT, Filtering, Image processing, nVidia, nVidia GeForce GTX 680, Package, Signal denoising

May 5, 2014 by hgpu

Accelerating Mixed-Abstraction SystemC Models on Multi-Core CPUs and GPUs

Anirudh Mohan Kaushik

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla C2075, Thesis

May 5, 2014 by hgpu

Coalition Structure Generation with the Graphics Processing Unit

Krzysztof Pawlowski, Karol Kurach, Kim Svensson, Sarvapali Ramchurn, Tomasz P. Michalak, Talal Rahwan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 660, Package, Performance

May 3, 2014 by hgpu

SUPERGLUE: A Shared Memory Framework Using Data Versioning for Dependency-Aware Task-Based Parallelization

Martin Tillenius

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Package, Task scheduling

April 29, 2014 by hgpu

Efficient Acceleration of Mutual Information Computation for Nonrigid Registration using CUDA

Kei Ikeda, Fumihiko Ino, Kenichi Hagihara

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Tags: CUDA, Image processing, Image registration, nVidia, nVidia GeForce GTX 580, Package

April 27, 2014 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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high performance computing on graphics processing units: hgpu.org

Packages

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Build and Travel KD-Tree with CUDA

Efficient Energyminimization in Finite-Difference Micromagnetics: Speeding up Hysteresis Computations

Geometric Algebra Enhanced Precompiler for C++, OpenCL and Mathematica’s OpenCLLink

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

Improving the Programmability of GPU Architectures

Non-separable 2D, 3D and 4D filtering with CUDA

Accelerating Mixed-Abstraction SystemC Models on Multi-Core CPUs and GPUs

Coalition Structure Generation with the Graphics Processing Unit

SUPERGLUE: A Shared Memory Framework Using Data Versioning for Dependency-Aware Task-Based Parallelization

Efficient Acceleration of Mutual Information Computation for Nonrigid Registration using CUDA

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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