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GPU Scripting and Code Generation with PyCUDA

Andreas Klockner, Nicolas Pinto, Bryan Catanzaro, Yunsup Lee, Paul Ivanov, Ahmed Fasih

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Package, PyOpenCL, Python

April 23, 2013 by hgpu

Computer Simulation of Saturn’s Ring Structure

Cole Kendrick

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Tags: Astrophysics, ATI, ATI Radeon HD 5850, Gravitation, MPI, N-body simulation, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Tesla S2050

April 21, 2013 by hgpu

OpenCL Fast Fourier Transform

Ruobing Li

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Tags: Computer science, FFT, nVidia, OpenCL, Package, Tesla M2070

April 9, 2013 by hgpu

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

R. Capuzzo-Dolcettaa, M. Spera

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Tags: Astrophysics, ATI, ATI Radeon HD 6970, ATI Radeon HD 7870, ATI Radeon HD 7970, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Tesla C1060, Tesla C2050, Tesla K20

April 9, 2013 by hgpu

Adapting Particle Filter Algorithms to Many-Core Architectures

Mehdi Chitchian, Alexander S. van Amesfoort, Andrea Simonetto, Tamas Keviczky, Henk J. Sips

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Tags: Algorithms, ATI, ATI Radeon HD 6970, ATI Radeon HD 7970, Bayesian, Computer science, Computer vision, CUDA, Filtering, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Particle filtering

April 4, 2013 by hgpu

C Language Extensions for Hybrid CPU/GPU Programming with StarPU

Ludovic Courtes

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Tags: Computer science, Hybrid computing, Mathematical Software, MPI, OpenCL, Package

April 4, 2013 by hgpu

High Performance Computing using GPGPU’s

Omar Usman Khan

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Tags: Electrodynamics, FFT, nVidia, nVidia GeForce GTX 260, OpenCL, Package, Thesis

March 29, 2013 by hgpu

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

Thibault Person, Francois Bodin

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Intel, Intel Phi, nVidia, OpenCL, Package, Performance, Portability, Tesla K20

March 24, 2013 by hgpu

Symbolic Crosschecking of Data-Parallel Floating Point Code

Peter Cyrus Collingbourne

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Tags: Algorithms, Compilers, Computer science, nVidia, OpenCL, Package, Tesla C1060, Thesis

March 20, 2013 by hgpu

clMAGMA: High Performance Dense Linear Algebra with OpenCL

Chongxiao Cao, Jack Dongarra, Peng Du, Mark Gates, Piotr Luszczek, Stanimire Tomov

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Package, Tesla S2050

March 18, 2013 by hgpu

Acceleration of the MMFF94 routines within OpenBabel using Eigen and OpenCL

Omar Valerio Minero

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Tags: Chemistry, Molecular modeling, OpenCL, Package, Thesis

February 28, 2013 by hgpu

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

S. J. Pennycook, S. A. Jarvis

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Tags: ATI, ATI FirePro V7800, ATI Radeon HD 6550, Benchmarking, Computer science, Molecular dynamics, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

February 14, 2013 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 Scripting and Code Generation with PyCUDA

Computer Simulation of Saturn’s Ring Structure

OpenCL Fast Fourier Transform

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

Adapting Particle Filter Algorithms to Many-Core Architectures

C Language Extensions for Hybrid CPU/GPU Programming with StarPU

High Performance Computing using GPGPU’s

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

Symbolic Crosschecking of Data-Parallel Floating Point Code

clMAGMA: High Performance Dense Linear Algebra with OpenCL

Acceleration of the MMFF94 routines within OpenBabel using Eigen and OpenCL

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

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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