high performance computing on graphics processing units: hgpu.org

Applications

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Feynman Machine: The Universal Dynamical Systems Computer

Eric Laukien, Richard Crowder, Fergal Byrne

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Tags: AMD Radeon R9 290, Artificial intelligence, ATI, Computer science, Deep learning, Mathematics, Neuroscience, OpenCL

September 20, 2016 by hgpu

Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

Yun Wu, Dimitrios S. Nikolopoulos, Roger Woods

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Tags: ARM, Benchmarking, Computer science, Energy-efficient computing, FPGA, Heterogeneous systems, OpenCL, OpenMP, SoC

September 20, 2016 by hgpu

Devito: automated fast finite difference computation

Navjot Kukreja, Mathias Louboutin, Felippe Vieira, Fabio Luporini, Michael Lange, Gerard Gorman

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Tags: Computer science, Finite difference, Intel Xeon Phi, OpenMP, Package

September 17, 2016 by hgpu

The CUDA LATCH Binary Descriptor: Because Sometimes Faster Means Better

Christopher Parker, Matthew Daiter, Kareem Omar, Gil Levi, Tal Hassner

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1080, Package

September 17, 2016 by hgpu

Parallel Dynamics Computation using Prefix Sum Operations

Yajue Yang, Yuanqing Wu, Jia Pan

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Tags: Computer science, CUDA, nVidia, Robotics, Tesla K40

September 17, 2016 by hgpu

A parallel pattern for iterative stencil + reduce

M. Aldinucci, M. Danelutto, M. Drocco, P. Kilpatrick, C. Misale, G. Peretti Pezzi, M. Torquati

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Tags: ARM, Computer science, nVidia, OpenCL, Stencil computation, Tesla K40, Tesla M2090

September 17, 2016 by hgpu

Efficient softmax approximation for GPUs

Edouard Grave, Armand Joulin, Moustapha Cisse, David Grangier, Herve Jegou

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Tags: Computer science, Deep learning, LSTM, Neural networks, NLP, nVidia, Tesla K40

September 17, 2016 by hgpu

Finding faint HI structure in and around galaxies: scraping the barrel

D. Punzo, J.M. van der Hulst, J.B.T.M. Roerdink

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Tags: Astrophysics, Filtering, Image processing, nVidia, nVidia GeForce GTX 860 M, OpenGL, OpenMP, Package, Visualization

September 17, 2016 by hgpu

Data Analysis of Minimally-Structured Heterogeneous Logs: An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes

Chang Liu

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Tags: Computer science, CUDA, Deep learning, LSTM, NLP, nVidia, Package, RNN, Thesis

September 13, 2016 by hgpu

OpenMP as a High-Level Specification Language for Parallelism And its use in Evaluating Parallel Programming Systems

Max Grossman, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, LLVM, nVidia, OpenMP, Package

September 13, 2016 by hgpu

An efficient numerical method for solving the Boltzmann equation in multidimensions

Giacomo Dimarco, Raphael Loubere, Jacek Narski, Thomas Rey

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Tags: Algorithms, Boltzmann equation, cfd, CUDA, Fluid dynamics, Mathematics, MPI, Numerical Analysis, nVidia, OpenMP, Physics

September 13, 2016 by hgpu

Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources

Olivier Beaumont, Terry Cojean, Lionel Eyraud-Dubois, Abdou Guermouche, Suraj Kumar

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40

September 13, 2016 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

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

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high performance computing on graphics processing units: hgpu.org

Applications

Feynman Machine: The Universal Dynamical Systems Computer

Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

Devito: automated fast finite difference computation

The CUDA LATCH Binary Descriptor: Because Sometimes Faster Means Better

Parallel Dynamics Computation using Prefix Sum Operations

A parallel pattern for iterative stencil + reduce

Efficient softmax approximation for GPUs

Finding faint HI structure in and around galaxies: scraping the barrel

Data Analysis of Minimally-Structured Heterogeneous Logs: An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes

OpenMP as a High-Level Specification Language for Parallelism And its use in Evaluating Parallel Programming Systems

An efficient numerical method for solving the Boltzmann equation in multidimensions

Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

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

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