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Object support for OpenMP-style programming of GPU clusters in Java

Carolin Wolf, Georg Dotzler, Ronald Veldema, Michael Philippsen

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Tags: Computer science, CUDA, GPU cluster, Java, nVidia, PC cluster, Tesla M1060

July 16, 2013 by hgpu

A framework for cost based optimization of hybrid CPU/GPU query plans in database systems

Sebastian Bress, Ingolf Geist, Eike Schallehn, Maik Mory, Gunter Saake

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia

July 15, 2013 by hgpu

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Dmitry Mikushin, Nikolay Likhogrud, Eddy Zheng Zhang, Christopher Bergstrom

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Tags: Code generation, Compilers, Computer science, CUDA, Fortran, nVidia, OpenACC, Package, PTX, Tesla K20

July 15, 2013 by hgpu

Parallelization of SAT Algorithms on GPUs

Carlos Costa

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Tags: Algorithms, Computer science, CUDA, nVidia, SAT

July 15, 2013 by hgpu

Exploiting Space and Time Coherence in Grid-based Sorting

Rubens Carlos Silva Oliveira, Claudio Esperanca, Antonio Oliveira

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Collision detection, Computer science, nVidia, nVidia GeForce GT 540 M, OpenCL, Particle simulation, Sorting

July 15, 2013 by hgpu

Near-LSPA Performance at MSA Complexity

Joao Andrade, Gabriel Falcao, Vitor Silva, Joao P. Barreto, Nuno Goncalves, Valentin Savin

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Tags: Computer science, CUDA, nVidia, Parity-check codes, Tesla M2050

July 15, 2013 by hgpu

Benchmarking Intel Xeon Phi to Guide Kernel Design

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips, Lilun Zhang, Yonggang Che, Chuanfu Xu

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Tags: Benchmarking, Computer science, Intel, Intel Phi, Performance

July 14, 2013 by hgpu

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Nicholas Wilt

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Tags: Book, Computer science, CUDA, Image processing, N-body simulation, nVidia, Overview, Package

July 13, 2013 by hgpu

Identifying the Key Features of Intel Xeon Phi: A Comparative Approach

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: Computer science, Intel, Intel Phi, Performance

July 13, 2013 by hgpu

Optimized MFCC Feature Extraction on GPU

Haofeng Kou, Weijia Shang, Ian Lane, Jike Chong

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Speech recognition

July 13, 2013 by hgpu

An acceleration of the algorithm for the nurse rerostering problem on a graphics processing unit

Zdenek Baumelt, Jan Dvorak, Premysl Sucha, Zdenek Hanzalek

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 650 Ti

July 13, 2013 by hgpu

Parallel Graph Processing on Graphics Processors Made Easy

Jianlong Zhong, Bingsheng He

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

July 12, 2013 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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high performance computing on graphics processing units: hgpu.org

Object support for OpenMP-style programming of GPU clusters in Java

A framework for cost based optimization of hybrid CPU/GPU query plans in database systems

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Parallelization of SAT Algorithms on GPUs

Exploiting Space and Time Coherence in Grid-based Sorting

Near-LSPA Performance at MSA Complexity

Benchmarking Intel Xeon Phi to Guide Kernel Design

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Identifying the Key Features of Intel Xeon Phi: A Comparative Approach

Optimized MFCC Feature Extraction on GPU

An acceleration of the algorithm for the nurse rerostering problem on a graphics processing unit

Parallel Graph Processing on Graphics Processors Made Easy

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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