high performance computing on graphics processing units: hgpu.org

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Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

Shinichi Yamagiwa, Guyue Wang, Koichi Wada

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Tags: Computer science, CUDA, nVidia, OpenCL, Tesla C2050

January 13, 2015 by hgpu

CHO: A Benchmark Suite for OpenCL-based FPGA Accelerators

Geoffrey Ndu, Mikel Lujan, Javier Navaridas

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Tags: Benchmarking, Computer science, FPGA, OpenCL, Package

January 8, 2015 by hgpu

An Extensible Framework for Composing Stencils with Common Scientific Computing Patterns

Leonard Truong, Chick Markley, Armando Fox

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Tags: Code generation, Computer science, OpenCL, Python

January 8, 2015 by hgpu

Performance and Power Comparisons Between Nvidia and ATI GPUs

Ying Zhang, Lu Peng, Bin Li, Jih-Kwon Peir, Jianmin Chen

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

January 8, 2015 by hgpu

Subdivision Surface Evaluation as Sparse Matrix-Vector Multiplication

Michael Driscoll

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Tags: 3D Graphics and Realism, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sparse matrix

January 5, 2015 by hgpu

Customization of OpenCL Applications for Efficient Task Mapping under Heterogeneous Platform Constraints

Edoardo Paone, Francesco Robino, Gianluca Palermo, Vittorio Zaccaria, Ingo Sander, Cristina Silvano

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia Quadro NVS 300, OpenCL, Performance

January 2, 2015 by hgpu

Performance comparison of Lattice Boltzmann fluid flow simulation using OpenCL and CUDA frameworks

Jelena Tekic, Predrag Tekic, Milos Rackovic

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Tags: Benchmarking, CUDA, Fluid dynamics, Heterogeneous systems, Java, Lattice Boltzmann model, nVidia, nVidia GeForce GT 220, OpenCL

January 2, 2015 by hgpu

Characterization of OpenCL on a Scalable FPGA Architecture

Shanyuan Gao, Jeremy Chritz

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Tags: AES, Computer science, FPGA, OpenCL

December 30, 2014 by hgpu

Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

Florentino Sainz, Sergi Mateo, Vicenc Beltran, Jose L. Bosque, Xavier Martorell, Eduard Ayguade

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Tags: Computer science, CUDA, Fortran, nVidia, OpenCL, Tesla M2050

December 30, 2014 by hgpu

Automatic Tuning of Local Memory Use on GPGPUs

Tianyi David Han, Tarek S. Abdelrahman

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Tags: Benchmarking, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla M2090

December 26, 2014 by hgpu

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

Lerato J. Mohapi, Simon Winberg, Michael Inggs

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Tags: Algorithms, CUDA, DSP, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Signal processing

December 22, 2014 by hgpu

PyFAI: a Python library for high performance azimuthal integration on GPU

Jerome Kieffer, Giannis Ashiotis

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Tags: Astrophysics, ATI, ATI FirePro V7800, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, nVidia, nVidia GeForce GTX 750 Ti, OpenCL, Package, PyOpenCL, Python, Tesla K20

December 22, 2014 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

Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

CHO: A Benchmark Suite for OpenCL-based FPGA Accelerators

An Extensible Framework for Composing Stencils with Common Scientific Computing Patterns

Performance and Power Comparisons Between Nvidia and ATI GPUs

Subdivision Surface Evaluation as Sparse Matrix-Vector Multiplication

Customization of OpenCL Applications for Efficient Task Mapping under Heterogeneous Platform Constraints

Performance comparison of Lattice Boltzmann fluid flow simulation using OpenCL and CUDA frameworks

Characterization of OpenCL on a Scalable FPGA Architecture

Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

Automatic Tuning of Local Memory Use on GPGPUs

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

PyFAI: a Python library for high performance azimuthal integration on GPU

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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