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AIvailable: A Software-Defined Architecture for LLM-as-a-Service on Heterogeneous and Legacy GPUs

Pedro Antunes, Ana Rita Ortigoso, Gabriel Vieira, Daniel Fuentes, Luís Frazão, Nuno Costa, António Pereira

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Tags: AMD Radeon Pro W6600, ATI, Computer science, CUDA, Heterogeneous systems, LLM, nVidia, nVidia GeForce GTX 1660, nVidia GeForce RTX 3070, ROCm

November 23, 2025 by hgpu

ProofWright: Towards Agentic Formal Verification of CUDA

Bodhisatwa Chatterjee, Drew Zagieboylo, Sana Damani, Siva Hari, Christos Kozyrakis

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Tags: Code generation, Computer science, CUDA, LLM, nVidia

November 23, 2025 by hgpu

Iris: First-Class Multi-GPU Programming Experience in Triton

Muhammad Awad, Muhammad Osama, Brandon Potter

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Tags: AMD Radeon Instinct MI300X, ATI, Benchmarking, Computer science, CUDA, HIP, nVidia, Package, Python, Triton

November 23, 2025 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

Inside VOLT: Designing an Open-Source GPU Compiler

Shinnung Jeong, Chihyo Ahn, Huanzhi Pu, Jisheng Zhao, Hyesoon Kim, Blaise Tine

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL

November 23, 2025 by hgpu

PRAGMA: A Profiling-Reasoned Multi-Agent Framework for Automatic Kernel Optimization

Kelun Lei, Hailong Yang, Huaitao Zhang, Xin You, Kaige Zhang, Zhongzhi Luan, Yi Liu, Depei Qian

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Tags: Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, Performance

November 16, 2025 by hgpu

MT4G: A Tool for Reliable Auto-Discovery of NVIDIA and AMD GPU Compute and Memory Topologies

Stepan Vanecek, Manuel Walter Mussbacher, Dominik Groessler, Urvij Saroliya, Martin Schulz

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI210, AMD Radeon Instinct MI300X, ATI, Benchmarking, Computer science, CUDA, HIP, nVidia, nVidia A100, nVidia GeForce RTX 2080, nVidia H100, nVidia Quadro P 6000, nVidia V100, Package, PTX

November 16, 2025 by hgpu

A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data

Zheng Li, Weiyan Wang, Ruiyuan Li, Chao Chen, Xianlei Long, Linjiang Zheng, Quanqing Xu, Chuanhui Yang

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Tags: Algorithms, Compression, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce RTX 5080, Package

November 16, 2025 by hgpu

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

Zijian Zhang, Rong Wang, Shiyang Li, Yuebo Luo, Mingyi Hong, Caiwen Ding

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, nVidia GeForce RTX 4090, nVidia RTX 6000 Ada, Package, Performance

November 9, 2025 by hgpu

RDMA Point-to-Point Communication for LLM Systems

Nandor Licker, Kevin Hu, Vladimir Zaytsev, Lequn Chen

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Tags: Computer science, CUDA, LLM, nVidia, nVidia H200, Package, Performance, RDMA

November 9, 2025 by hgpu

AMD MI300X GPU Performance Analysis

Chandrish Ambati, Trung Diep

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Tags: AMD Radeon Instinct MI300X, ATI, Benchmarking, Computer science, CUDA, HIP, nVidia, nVidia H100, Performance

November 9, 2025 by hgpu

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

Brandon Alexander Burtchell, Martin Burtscher

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Tags: Algorithms, Compilers, Compression, Computer science, CUDA, HIP, nVidia, nVidia GeForce GTX Titan V, nVidia GeForce RTX 3080 Ti, nVidia GeForce RTX 4090, Package

November 9, 2025 by hgpu

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

OpScanner

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

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high performance computing on graphics processing units: hgpu.org

AIvailable: A Software-Defined Architecture for LLM-as-a-Service on Heterogeneous and Legacy GPUs

ProofWright: Towards Agentic Formal Verification of CUDA

Iris: First-Class Multi-GPU Programming Experience in Triton

The Anatomy of a Triton Attention Kernel

Inside VOLT: Designing an Open-Source GPU Compiler

PRAGMA: A Profiling-Reasoned Multi-Agent Framework for Automatic Kernel Optimization

MT4G: A Tool for Reliable Auto-Discovery of NVIDIA and AMD GPU Compute and Memory Topologies

A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

RDMA Point-to-Point Communication for LLM Systems

AMD MI300X GPU Performance Analysis

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

Recent source codes

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

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