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Adaptive Dynamic Load Balancing in Heterogeneous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search

Trong-Tuan Vu, Bilel Derbel, Nouredine Melab

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Performance, Tesla T10

January 14, 2013 by hgpu

A Multi-GPU Programming Library for Real-Time Applications

Sebastian Schaetz, Martin Uecker

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Tags: Algorithms, CUDA, GPU cluster, Image reconstruction, Magnetic resonance imaging, MPI, MRI, nVidia, nVidia GeForce GTX 580, Performance, Signal processing

January 8, 2013 by hgpu

Performance comparison of gauss-Jordan elimination method using OpenMP and CUDA

Baha Sen, Nesrin Aydin Atasoy, Caner Ozcan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, OpenMP, Performance, Programming techniques

January 7, 2013 by hgpu

uBench: Performance Impact of CUDA Block Geometry

Yuri Torres, Arturo Gonzalez, Diego R. Llanos

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

January 3, 2013 by hgpu

KFusion: Obtaining Modularity and Performance with Regards to General Purpose GPU Computing and Co-processors

Liam Kiemele

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Tags: Compilers, Computer science, nVidia, OpenCL, Package, Performance, Tesla C2075, Thesis

December 20, 2012 by hgpu

An Automatic Host and Device Memory Allocation Method for OpenMPC

Hiroaki Uchiyama, Tomoaki Tsumura, Hiroshi Matsuo

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, OpenMP, Performance, Tesla C1060

December 20, 2012 by hgpu

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Shoaib Ashraf Kamil

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques, Thesis

December 16, 2012 by hgpu

Vectorized Higher Order Finite Difference Kernels

Gerhard Zumbusch

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Tags: Algorithms, ATI, ATI Radeon HD 6990, ATI Radeon HD 7970, Computer science, Finite difference, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C2050, Tesla K20

December 10, 2012 by hgpu

Neither More Nor Less: Optimizing Thread-level Parallelism for GPGPUs

Onur Kayiran, Adwait Jog, Mahmut T. Kandemir, Chita R. Das

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Tags: Computer science, CUDA, nVidia, Performance

December 10, 2012 by hgpu

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

Tim Cramer, Dirk Schmidl, Michael Klemm, Dieter an Mey

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

December 8, 2012 by hgpu

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

Tiark Rompf

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Software Engineering, Tesla C2050, Thesis

December 8, 2012 by hgpu

FusionSim: Characterizing the Performance Benefits of Fused CPU/GPU Systems

Vitaly Zakharenko

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Tags: AMD Fusion, Analytical model, Benchmarking, Computer science, Package, Performance, Thesis

December 4, 2012 by hgpu

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

See all packages

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high performance computing on graphics processing units: hgpu.org

Adaptive Dynamic Load Balancing in Heterogeneous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search

A Multi-GPU Programming Library for Real-Time Applications

Performance comparison of gauss-Jordan elimination method using OpenMP and CUDA

uBench: Performance Impact of CUDA Block Geometry

KFusion: Obtaining Modularity and Performance with Regards to General Purpose GPU Computing and Co-processors

An Automatic Host and Device Memory Allocation Method for OpenMPC

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Vectorized Higher Order Finite Difference Kernels

Neither More Nor Less: Optimizing Thread-level Parallelism for GPGPUs

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

FusionSim: Characterizing the Performance Benefits of Fused CPU/GPU Systems

Recent source codes

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

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