high performance computing on graphics processing units: hgpu.org

Massinissa Merouani, Khaled Afif Boudaoud, Iheb Nassim Aouadj, Nassim Tchoulak, Islam Kara Bernou, Hamza Benyamina, Fatima Benbouzid-Si Tayeb, Karima Benatchba, Hugh Leather, Riyadh Baghdadi

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Tags: Compilers, Computer science, Deep learning, Machine learning, OpenCL, Package, Programming Languages

March 24, 2024 by hgpu

An Autonomous Data Language

Tom T.P. Franken, Thomas Neele, Jan Friso Groote

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Programming Languages

January 7, 2024 by hgpu

Gaiwan: a Size-Polymorphic Typesystem for GPU Programs

Robbert Gurdeep Singha, Christophe Scholliers

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, OpenCL, Package, Programming Languages

December 31, 2023 by hgpu

Experiences Building an MLIR-based SYCL Compiler

Ettore Tiotto, Víctor Pérez, Whitney Tsang, Lukas Sommer, Julian Oppermann, Victor Lomüller, Mehdi Goli, James Brodman

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Tags: Compilers, Computer science, Heterogeneous systems, Performance, Programming Languages, SYCL

December 24, 2023 by hgpu

Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Wenhua Yang, Chong Zhang, Minxue Pan

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Tags: Computer science, CUDA, nVidia, OpenCL, Programming Languages, survey

December 10, 2023 by hgpu

Reverse-Mode AD of Reduce-by-Index and Scan in Futhark

Lotte Maria Bruun, Ulrik Stuhr Larsen, Nikolaj Hinnerskov, Cosmin Oancea

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Tags: Computer science, nVidia, nVidia A100, Programming Languages

October 15, 2023 by hgpu

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

pyATF: Constraint-Based Auto-Tuning in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

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high performance computing on graphics processing units: hgpu.org

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Finding Missed Code Size Optimizations in Compilers using LLMs

Scheduling Languages: A Past, Present, and Future Taxonomy

Testing GPU Numerics: Finding Numerical Differences Between NVIDIA and AMD GPUs

A Comparison of OpenCL, CUDA, and HIP as Compilation Targets for a Functional Array Language

GPU Implementations for Midsize Integer Addition and Multiplication

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

An Autonomous Data Language

Gaiwan: a Size-Polymorphic Typesystem for GPU Programs

Experiences Building an MLIR-based SYCL Compiler

Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Reverse-Mode AD of Reduce-by-Index and Scan in Futhark

Recent source codes

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

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