high performance computing on graphics processing units: hgpu.org

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Performance Counters based Power Modeling of Mobile GPUs using Deep Learning

Nadjib Mammeri, Markus Neu, Sohan Lal, Ben Juurlink

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Tags: Computer science, Deep learning, Energy-efficient computing, Heterogeneous systems, Neural networks, OpenCL, OpenGL, SoC

February 23, 2020 by hgpu

High-Performance High-Order Stencil Computation on FPGAs Using OpenCL

Hamid Reza Zohouri, Artur Podobas, Satoshi Matsuoka

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Tags: Computer science, FPGA, OpenCL, Stencil computation

February 23, 2020 by hgpu

EASYPAP: a Framework for Learning Parallel Programming

Alice Lasserre, Raymond Namyst, Pierre-André Wacrenier

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Tags: Algorithms, AVX, Computer science, Education, MPI, OpenCL, OpenMP, Package, Pthreads

February 16, 2020 by hgpu

Automated Runtime Analysis and Adaptation for Scalable Heterogeneous Computing

Ahmed E. Helal

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Tags: Computer science, CUDA, HPC, nVidia, OpenCL, OpenMP, Package, Performance, Tesla M2050, Thesis

February 9, 2020 by hgpu

A Language for Describing Optimization Strategies

Bastian Hagedorn, Johannes Lenfers, Thomas Koehler, Sergei Gorlatch, Michel Steuwer

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Tags: Computer science, DSL, High-level Languages, OpenCL, Package, Scala

February 9, 2020 by hgpu

MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

Ji Liu, Abdullah-Al Kafi, Xipeng Shen, Huiyang Zhou

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Tags: Compilers, Computer science, FPGA, nVidia, nVidia GeForce RTX 2080, OpenCL, Performance

February 9, 2020 by hgpu

GPU-accelerated dynamic programming for join-order optimization

Andreas Meister, Gunter Saake

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Tags: Computer science, Databases, nVidia, OpenCL, Tesla K20

February 2, 2020 by hgpu

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

Bérenger Bramas, Philippe Helluy, Laura Mendoza, Bruno Weber

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Tags: Algorithms, Mathematics, nVidia, nVidia GeForce GTX 1050, OpenCL, Package, PDEs, Tesla P100

February 2, 2020 by hgpu

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

Donatella Granata, Angelo Palombo, Federico Santini, Umberto Amato

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Tags: Algorithms, Heterogeneous systems, nVidia, nVidia GeForce GTX 1650, OpenCL, Sensing, Signal processing

February 2, 2020 by hgpu

Using Parallel Programming Models for Automotive Workloads on Heterogeneous Systems – a Case Study

Lukas Sommer, Florian Stock, Leonardo Solis-Vasquez, Andreas Koch

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Tags: Automotive, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson TX2, OpenCL, OpenMP

January 26, 2020 by hgpu

Hardware/Software Co-Design for Data-Intensive Genomics Workloads

Nicola Cadenelli

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Tags: Algorithms, Computer science, FPGA, nVidia, OpenCL, performance portability, Tesla K40, Thesis

January 26, 2020 by hgpu

Automatically Harnessing Sparse Acceleration

Philip Ginsbach, Bruce Collie, Michael F.P. O'Boyle

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Tags: AMD Radeon R7, ATI, Computer science, CUDA, Fortran, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, OpenCL, Performance

January 26, 2020 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

Performance Counters based Power Modeling of Mobile GPUs using Deep Learning

High-Performance High-Order Stencil Computation on FPGAs Using OpenCL

EASYPAP: a Framework for Learning Parallel Programming

Automated Runtime Analysis and Adaptation for Scalable Heterogeneous Computing

A Language for Describing Optimization Strategies

MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

GPU-accelerated dynamic programming for join-order optimization

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

Using Parallel Programming Models for Automotive Workloads on Heterogeneous Systems – a Case Study

Hardware/Software Co-Design for Data-Intensive Genomics Workloads

Automatically Harnessing Sparse Acceleration

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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