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AKG kernel Agent: A Multi-Agent Framework for Cross-Platform Kernel Synthesis

Jinye Du, Quan Yuan, Zuyao Zhang, Yanzhi Yi, Jiahui Hu, Wangyi Chen, Yiyang Zhu, Qishui Zheng, Wenxiang Zou, Xiangyu Chang, Zuohe Zheng, Zichun Ye, Chao Liu, Shanni Li, Renwei Zhang, Yiping Deng, Xinwei Hu, Xuefeng Jin, Jie Zhao

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Tags: Code generation, Computer science, CUDA, DSL, LLM, nVidia, nVidia A100, Triton

January 12, 2026 by hgpu

The Anatomy of a Triton Attention Kernel

Burkhard Ringlein, Jan van Lunteren, Radu Stoica, Thomas Parnell

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Tags: AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, ATI, Computer science, CUDA, DSL, HIP, LLM, nVidia, nVidia H100, Performance, Programming Languages, Triton

November 23, 2025 by hgpu

GPU Performance Portability needs Autotuning

Burkhard Ringlein, Thomas Parnell, Radu Stoica

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Tags: AMD Radeon Instinct MI250, ATI, Auto-Tuning, Computer science, CUDA, DSL, HIP, LLM, nVidia, nVidia A100, Performance, performance portability

May 18, 2025 by hgpu

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

Anjiang Wei, Allen Nie, Thiago S. F. X. Teixeira, Rohan Yadav, Wonchan Lee, Ke Wang, Alex Aiken

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Tags: Code generation, Computer science, DSL, LLM, Matrix multiplication, nVidia, Optimization, Tesla P100

November 17, 2024 by hgpu

A domain-specific language for geospatial computations on the GPU

Louise Tidestav

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Tags: Computer science, CUDA, DSL, nVidia, nVidia Quadro P 2000, Thesis

October 13, 2024 by hgpu

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

Ruixin Wang, Minghai Lu, Cody Hao Yu, Yi-Hsiang Lai, Tianyi Zhang

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Tags: Computer science, CUDA, Deep learning, DSL, nVidia, Package, Performance, PyTorch, Tesla T4

May 12, 2024 by hgpu

Code Generation for a Variety of Accelerators for a Graph DSL

Ashwina Kumar, M. Venkata Krishna, Prasanna Bartakke, Rahul Kumar, Rajesh Pandian M, Nibedita Behera, Rupesh Nasre

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Tags: Code generation, Computer science, CUDA, DSL, nVidia, nVidia GeForce RTX 2080 Ti, OpenACC, OpenCL, Package, SYCL, Tesla V100

January 14, 2024 by hgpu

A Domain-Extensible Compiler with Controllable Automation of Optimisations

Thomas Kœhler

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Tags: Code generation, Computer science, DSL, Heterogeneous systems, Image processing, Machine learning, OpenCL, Package, Thesis

January 8, 2023 by hgpu

Analysis of High Level implementations for Recursive Methods on GPUs

Cheng Cao, Justin Kalloor

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Tags: Computer science, CUDA, DSL, nVidia, nVidia GeForce RTX 3080, OpenGL, Vulkan

January 9, 2022 by hgpu

GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity

Wei Niu, Zhengang Li, Xiaolong Ma, Peiyan Dong, Gang Zhou, Xuehai Qian, Xue Lin, Yanzhi Wang, Bin Ren

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Tags: Artificial intelligence, Code generation, Computer science, Deep learning, DSL, Neural networks, nVidia, nVidia Titan RTX, OpenCL

August 29, 2021 by hgpu

A Compiler Infrastructure for Accelerator Generators

Rachit Nigam, Samuel Thomas, Zhijing Li, Adrian Sampson

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Tags: Compilers, Computer science, DSL, Hardware Architecture, HLS, Package, Programming Languages

March 14, 2021 by hgpu

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Biagio Cosenza, Nikita Popov, Ben Juurlink, Paul Richmond, Mozhgan Kabiri Chimeh, Carmine Spagnuolo, Gennaro Cordasco, Vittorio Scarano

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Tags: Compilers, Computer science, CUDA, DSL, nVidia, nVidia GeForce GTX Titan XP, Package

January 24, 2021 by hgpu

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high performance computing on graphics processing units: hgpu.org

AKG kernel Agent: A Multi-Agent Framework for Cross-Platform Kernel Synthesis

The Anatomy of a Triton Attention Kernel

GPU Performance Portability needs Autotuning

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

A domain-specific language for geospatial computations on the GPU

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

Code Generation for a Variety of Accelerators for a Graph DSL

A Domain-Extensible Compiler with Controllable Automation of Optimisations

Analysis of High Level implementations for Recursive Methods on GPUs

GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity

A Compiler Infrastructure for Accelerator Generators

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Recent source codes

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