high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Performance Portability in Accelerated Parallel Kernels

John A. Stratton, Hee-Seok Kim, Thoman B. Jablin, Wen-Mei W. Hwu

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Tags: Computer science, Heterogeneous systems, OpenCL, OpenMP, Performance

May 27, 2013 by hgpu

A Performance Modeling and Optimization Analysis Tool for Sparse Matrix-Vector Multiplication on GPUs

Ping Guo, Liqiang Wang, Po Chen

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 27, 2013 by hgpu

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Konstantinos Menychtas, Kai Shen, Michael L. Scott

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 670, nVidia Quadro NVS 295, Performance

May 25, 2013 by hgpu

Stencil and Lattice Structures for Field Equation Model Simulations on GPUs

D.P. Playne, K.A. Hawick

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Tags: Code generation, Computer science, CUDA, Field equations, nVidia, nVidia GeForce GTX 580

May 25, 2013 by hgpu

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

Hector Ortega-Arranz, Yuri Torres, Diego R. Llanos, Arturo Gonzalez-Escribano

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 480

May 25, 2013 by hgpu

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K. A. Hawick, D. P. Playne

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

May 25, 2013 by hgpu

OpenCL Performance Evaluation on Modern Multi Core CPUs

Joo Hwan Lee, Kaushik Patel, Nimit Nigania, Hyojong Kim, Hyesoon Kim

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

May 25, 2013 by hgpu

GEMTC: GPU Enabled Many-Task Computing

Scott Krieder, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 670, Performance

May 25, 2013 by hgpu

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

A.-E Hugo A. Guermouche P.-A. Wacrenier R. Namyst

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Tesla M2070

May 23, 2013 by hgpu

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Derek R. Hower, Bradford M. Beckmann, Benedict R. Gaster, Blake A. Hechtman, Mark D. Hill, Steven K. Reinhardt, David A. Wood

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Performance

May 23, 2013 by hgpu

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Salvatore Cuomo, Ardelio Gallettiy, Giulio Giuntay, Alfredo Staracey

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Tesla C1060

May 23, 2013 by hgpu

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Simon John Pennycook

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Source codes

Tags: Algorithms, ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GT, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C1060, Tesla C2050, Thesis

May 21, 2013 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

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

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

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

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

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Applications

Performance Portability in Accelerated Parallel Kernels

A Performance Modeling and Optimization Analysis Tool for Sparse Matrix-Vector Multiplication on GPUs

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Stencil and Lattice Structures for Field Equation Model Simulations on GPUs

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

OpenCL Performance Evaluation on Modern Multi Core CPUs

GEMTC: GPU Enabled Many-Task Computing

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Recent source codes

Kernel Library for LLM Serving

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

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

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

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

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