high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Fast and Memory-Efficient Minimum Spanning Tree on the GPU

Scott Rostrup, Shweta Srivastava, Kishore Singhal

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Tags: Algorithms, Computer science, Graph theory, nVidia, Performance, Tesla S1070, Tesla T10

December 10, 2011 by hgpu

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Qiang Liu, Wayne Luk

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Performance, Tesla C2070

December 9, 2011 by hgpu

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Petr Pospichal

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, nVidia, nVidia GeForce GTX 480, Performance

December 7, 2011 by hgpu

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

Jan Fousek, Jiri Filipovic, Matus Madzin

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

December 6, 2011 by hgpu

Performance Analysis of GPU compared to Single-core and Multi-core CPU for Natural Language Applications

Shubham Gupta, M.Rajasekhara Babu

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GT 210 M, OpenMP, Performance, String matching

December 6, 2011 by hgpu

Performance engineering for the Lattice Boltzmann method on GPGPUs: Architectural requirements and performance results

Johannes Habich, Christian Feichtinger, Harald Kostler, Georg Hager, Gerhard Wellein

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Tags: Algorithms, ATI, ATI Radeon HD 6970, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce 8800 GTX, OpenCL, Optimization, Performance, Tesla C1060, Tesla C2070

December 6, 2011 by hgpu

GMM based Fisher vector calculation on GPGPU

Erik Bodzsar, Balint Daroczy, Istvan Petras, Andras A. Benczur

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Source codes

Tags: Clustering, CUDA, Databases, Image processing, nVidia, nVidia GeForce GTX 285, Package, Performance, SIFT

December 5, 2011 by hgpu

GROPHECY: GPU performance projection from CPU code skeletons

Jiayuan Meng, Vitali A. Morozov, Kalyan Kumaran, Venkatram Vishwanath, Thomas D. Uram

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Tags: Analytical model, Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, Performance, Tesla C1060

December 5, 2011 by hgpu

Performance and numerical accuracy evaluation of heterogeneous multicore systems for Krylov orthogonal basis computation

Jerome Dubois, Christophe Calvin, Serge Petiton

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Tags: Cell processor, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla C1060

November 30, 2011 by hgpu

Applications Performance on GPGPUs with the Fermi Architecture

Ahmed Mohamed Hassan Abdalla

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, Performance, Tesla C2050, Tesla M1060, Thesis

November 29, 2011 by hgpu

Solving Dense Generalized Eigenproblems on Multi-threaded Architectures

Jose I. Aliaga, Paolo Bientinesi, Davor Davidovic, Edoardo Di Napoli, Francisco D. Igual, Enrique S. Quintana-Orti

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Tags: Computer science, CUDA, Linear Algebra, Mathematical Software, Molecular dynamics, nVidia, Performance, Tesla C2050

November 29, 2011 by hgpu

Partitioned Memory Parallel Programming Framework

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, Memory, nVidia, Performance, Tesla C1060

November 26, 2011 by hgpu

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

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high performance computing on graphics processing units: hgpu.org

Fast and Memory-Efficient Minimum Spanning Tree on the GPU

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

Performance Analysis of GPU compared to Single-core and Multi-core CPU for Natural Language Applications

Performance engineering for the Lattice Boltzmann method on GPGPUs: Architectural requirements and performance results

GMM based Fisher vector calculation on GPGPU

GROPHECY: GPU performance projection from CPU code skeletons

Performance and numerical accuracy evaluation of heterogeneous multicore systems for Krylov orthogonal basis computation

Applications Performance on GPGPUs with the Fermi Architecture

Solving Dense Generalized Eigenproblems on Multi-threaded Architectures

Partitioned Memory Parallel Programming Framework

Recent source codes

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

TRUST: a thermalhydraulic software package for CFD simulations

Modular: The Modular Platform (includes MAX & Mojo)

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

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