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Memory-Efficient Object-Oriented Programming on GPUs

Matthias Springer

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 940 M, nVidia GeForce GTX 980, nVidia GeForce GTX Titan XP, Package, Programming Languages, Thesis

August 25, 2019 by hgpu

Efficient Simulation of Fluid Flow and Transport in Heterogeneous Media Using Graphics Processing Units (GPUs)

Hassan Dashtian, Muhammad Sahimi

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Tags: Computational Physics, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 880, Physics

August 18, 2019 by hgpu

High Performance Computing via High Level Synthesis

Mehdi Roozmeh

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Tags: Computer science, Design space exploration, FPGA, Heterogeneous systems, HLS, Nearest neighbour, nVidia, OpenCL, Package, Signal processing, Thesis

August 18, 2019 by hgpu

Visual Analysis Algorithms for Embedded Systems

Syed Tahir Hussain Rizvi

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Jetson K1, nVidia Jetson TX1, Thesis

August 18, 2019 by hgpu

SODECL: An Open Source Library for Calculating Multiple Orbits of a System of Stochastic Differential Equations in Parallel

Eleftherios Avramidis, Marta Lalik, Ozgur E. Akman

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Tags: AMD FirePro W8100, ATI, Computer science, Differential equations, Mathematical Software, nVidia, OpenCL, Package, Tesla V100

August 18, 2019 by hgpu

Simple Iterative Incompressible Smoothed Particle Hydrodynamics

Abhinav Muta, Prabhu Ramachandran, Pawan Negi

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Tags: Benchmarking, Computational Physics, Fluid dynamics, Laplace and Poisson equation, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1070 Ti, OpenCL, Package, Poisson equation

August 11, 2019 by hgpu

A Deep Learning Approach for Automatic Code Optimization in the Tiramisu Compiler

Mohammed Henni, Ilhem Isra Mekki

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Tags: Code generation, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia DGX-1

August 11, 2019 by hgpu

Performance Comparison for Neuroscience Application Benchmarks

Andreas Herten, Thorsten Hater, Wouter Klijn, Dirk Pleiter

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Tags: Benchmarking, Computer science, CUDA, Neuroscience, nVidia, Performance, Tesla P100, Tesla V100

August 11, 2019 by hgpu

GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU

Carl Yang, Aydin Buluc, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Package, Tesla K40

August 11, 2019 by hgpu

Incremental Bounded Model Checking of Artificial Neural Networks in CUDA

Luiz H. Sena, Iury V. Bessa, Mikhail R. Gadelha, Lucas C. Cordeiro, Edjard Mota

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Tags: Computer science, CUDA, Neural networks, nVidia, Package

August 5, 2019 by hgpu

GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation

Shaoyi Peng, Sheldon X.-D. Tan

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX Titan X, Sparse matrix

August 5, 2019 by hgpu

A Power Efficient Neural Network Implementation on Heterogeneous FPGA and GPU Devices

Yuexuan Tu, Saad Sadiq, Yudong Tao, Mei-Ling Shyu, Shu-Ching Chen

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Tags: Computer science, Deep learning, Energy-efficient computing, FPGA, Neural networks, nVidia, nVidia Jetson TX2

July 28, 2019 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Memory-Efficient Object-Oriented Programming on GPUs

Efficient Simulation of Fluid Flow and Transport in Heterogeneous Media Using Graphics Processing Units (GPUs)

High Performance Computing via High Level Synthesis

Visual Analysis Algorithms for Embedded Systems

SODECL: An Open Source Library for Calculating Multiple Orbits of a System of Stochastic Differential Equations in Parallel

Simple Iterative Incompressible Smoothed Particle Hydrodynamics

A Deep Learning Approach for Automatic Code Optimization in the Tiramisu Compiler

Performance Comparison for Neuroscience Application Benchmarks

GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU

Incremental Bounded Model Checking of Artificial Neural Networks in CUDA

GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation

A Power Efficient Neural Network Implementation on Heterogeneous FPGA and GPU Devices

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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