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GPU computing with OpenCL to model 2D elastic wave propagation: exploring memory usage

Ursula Iturraran-Viveros, Miguel Molero-Armenta

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Tags: Condensed matter, Instrumentation and measurement, nVidia, OpenCL, Package, Physics, PyOpenCL, Python

August 21, 2015 by hgpu

A Parallel Implementation of the Self Organising Map using OpenCL

Gavin Davidson

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Tags: Algorithms, Computer science, Machine learning, nVidia, nVidia GeForce GTX 590, OpenCL, Package, Self-organizing map

August 11, 2015 by hgpu

Efficient Convolutional Patch Networks for Scene Understanding

Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler

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Tags: CNN, Computer science, Deep learning, Machine learning, OpenCL, Package

July 24, 2015 by hgpu

Parallel Programming in Actor-Based Applications via OpenCL

Paul Harvey, Kristian Hentschel, Joseph Sventek

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Tags: AMD Radeon R9 290X, ATI, Computer science, OpenACC, OpenCL, Package, Performance

July 20, 2015 by hgpu

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

Mark James Abraham, Teemu Murtola, Roland Schulz, Szilard Pall, Jeremy C. Smith, Berk Hess, Erik Lindahl

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Tags: Algorithms, Biomolecules, Chemistry, CUDA, Heterogeneous systems, Molecular simulation, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Tesla K40

July 20, 2015 by hgpu

Concurrent Manipulation of Dynamic Data Structures in OpenCL

Henk Mulder

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Tags: Algorithms, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GT 310 M, OpenCL, Package

July 15, 2015 by hgpu

Optimization, Specification and Verification of the Prefix Sum Program in an OpenCL Environment

Thijs Wiefferink

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 770, OpenCL, Package

July 13, 2015 by hgpu

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Anton Akusok, Kaj-Mikael Bjork, Yoan Miche, Amaury Lendasse

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, OpenCL, Package, Python

July 6, 2015 by hgpu

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

Lucas Benedicic

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Tags: Algorithms, Cellular automata, Metaheuristics, nVidia, nVidia GeForce GTX 660 Ti, OpenCL, Package, Signal processing, Thesis

June 22, 2015 by hgpu

Accelerating parameter synthesis for stochastic models

Petr Pilar

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Probability, Sparse matrix, Thesis

June 14, 2015 by hgpu

Improving OpenCL Programmability with the Heterogeneous Programming Library

Moises Vinas, Basilio B. Fraguela, Zeki Bozkus, Diego Andrade

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla C2050

June 8, 2015 by hgpu

Lensed: a code for the forward reconstruction of lenses and sources from strong lensing observations

Nicolas Tessore, Fabio Bellagamba, R. Benton Metcalf

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Tags: Astrophysics, OpenCL, Package, Rendering

May 29, 2015 by hgpu

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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high performance computing on graphics processing units: hgpu.org

Programming

GPU computing with OpenCL to model 2D elastic wave propagation: exploring memory usage

A Parallel Implementation of the Self Organising Map using OpenCL

Efficient Convolutional Patch Networks for Scene Understanding

Parallel Programming in Actor-Based Applications via OpenCL

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

Concurrent Manipulation of Dynamic Data Structures in OpenCL

Optimization, Specification and Verification of the Prefix Sum Program in an OpenCL Environment

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

Accelerating parameter synthesis for stochastic models

Improving OpenCL Programmability with the Heterogeneous Programming Library

Lensed: a code for the forward reconstruction of lenses and sources from strong lensing observations

Recent source codes

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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