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Opt: A Domain Specific Language for Non-linear Least Squares Optimization in Graphics and Imaging

Zachary DeVito, Michael Mara, Michael Zollhofer, Gilbert Bernstein, Jonathan Ragan-Kelley, Christian Theobalt, Pat Hanrahan, Matthew Fisher, Matthias Niessner

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Tags: Comnputer science, Computer vision, CUDA, Image generation, Image processing, nVidia, Programming Languages

April 26, 2016 by hgpu

High-level GPU programming in Julia

Tim Besard, Pieter Verstraete, Bjorn De Sutter

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Tags: Code generation, Compilers, Computer science, CUDA, LLVM, nVidia, nVidia GeForce GTX Titan, Programming Languages

April 14, 2016 by hgpu

Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

Guillermo Vigueras, Manuel Carro, Salvador Tamarit, Julio Marino

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Tags: Computer science, Heterogeneous systems, Machine learning, OpenCL, Programming Languages

March 15, 2016 by hgpu

Revisiting Actor Programming in C++

Dominik Charousset, Raphael Hiesgen, Thomas C. Schmidt

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Tags: Algorithms, Computer science, Heterogeneous systems, MPI, nVidia, OpenCL, OpenMPI, Package, Programming Languages, Tesla C2075

May 28, 2015 by hgpu

Locally-Oriented Programming: A Simple Programming Model for Stencil-Based Computations on Multi-Level Distributed Memory Architectures

Craig Rasmussen, Matthew Sottile, Daniel Nagle, Soren Rasmussen

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Tags: Computer science, OpenCL, Programming Languages

February 13, 2015 by hgpu

Patterns and Rewrite Rules for Systematic Code Generation (From High-Level Functional Patterns to High-Performance OpenCL Code)

Michel Steuwer, Christian Fensch, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Programming Languages

February 10, 2015 by hgpu

C++ AMP: Accelerated Massive Parallelism with Microsoft Visual C++

Kate Gregory, Ade Miller

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Tags: Book, C++ AMP, Programming Languages

December 13, 2014 by AlexVlx

IPMACC: Open Source OpenACC to CUDA/OpenCL Translator

Ahmad Lashgar, Alireza Majidi, Amirali Baniasadi

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Tags: Computer science, CUDA, nVidia, OpenACC, OpenCL, Programming Languages, Tesla K20

December 5, 2014 by hgpu

Enhancing R with Advanced Compilation Tools and Methods

Duncan Temple Lang

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Tags: Computer science, CUDA, Mathematical Software, nVidia, Programming Languages

September 11, 2014 by hgpu

ADHA: Automatic Data layout framework for Heterogeneous Architectures

Deepak Majeti, Kuldeep S. Meel, Rajkishore Barik, Vivek Sarkar

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Tags: Benchmarking, Compilers, Computer science, Heterogeneous systems, nVidia, OpenCL, Programming Languages, Tesla M2050

July 24, 2014 by hgpu

Loo.py: transformation-based code generation for GPUs and CPUs

Andreas Klockner

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Tags: ATI, ATI Radeon HD 7990, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, Programming Languages, PyOpenCL, Python

June 2, 2014 by hgpu

Augur: a Modeling Language for Data-Parallel Probabilistic Inference

Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Pocock, Stephen J. Green, Guy L. Steele Jr

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Tags: Bayesian, CUDA, Machine learning, Mathematics, nVidia, nVidia GeForce GTX Titan, Programming Languages, Statistics

December 13, 2013 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Opt: A Domain Specific Language for Non-linear Least Squares Optimization in Graphics and Imaging

High-level GPU programming in Julia

Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

Revisiting Actor Programming in C++

Locally-Oriented Programming: A Simple Programming Model for Stencil-Based Computations on Multi-Level Distributed Memory Architectures

Patterns and Rewrite Rules for Systematic Code Generation (From High-Level Functional Patterns to High-Performance OpenCL Code)

C++ AMP: Accelerated Massive Parallelism with Microsoft Visual C++

IPMACC: Open Source OpenACC to CUDA/OpenCL Translator

Enhancing R with Advanced Compilation Tools and Methods

ADHA: Automatic Data layout framework for Heterogeneous Architectures

Loo.py: transformation-based code generation for GPUs and CPUs

Augur: a Modeling Language for Data-Parallel Probabilistic Inference

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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