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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

Tutoring LLM into a Better CUDA Optimizer

Matyáš Brabec, Jiří Klepl, Michal Töpfer, Martin Kruliš

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Tags: Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, nVidia H100, nVidia V100, Package

October 26, 2025 by hgpu

BePilot: An AI Programming Assistant for Compiler Backend Development

Ming Zhong, Xin Sun, Fang Lv, Lulin Wang, Hongna Geng, Lei Qiu, Huimin Cui, Xiaobing Feng

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Tags: AI, Code generation, Compilers, Computer science, LLM, nVidia, nVidia A100, nVidia V100

August 31, 2025 by hgpu

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

Antonio De Caro, Gennaro Cordasco, Federico Ficarelli, Biagio Cosenza

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Tags: Biology, Chemistry, Computer science, CUDA, MPI, nVidia, nVidia V100, oneAPI, Package

August 10, 2025 by hgpu

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Paul Cardosi, Bérenger Bramas

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Tags: Computer science, CUDA, Heterogeneous systems, HIP, nVidia, nVidia A100, nVidia P100, nVidia Quadro RTX 8000, nVidia V100, Package, Task scheduling

July 20, 2025 by hgpu

LiteGD: Lightweight and dynamic GPU Dispatching for Large-scale Heterogeneous Clusters

Kunming Zhang, Hanlong Liao, Guoming Tang

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Tags: Computer science, GPU cluster, Heterogeneous systems, Machine learning, nVidia, nVidia A800, nVidia GeForce RTX 4090, nVidia H100, nVidia RTX A6000, nVidia V100

June 22, 2025 by hgpu

Acceleration as a Service (XaaS) Source Containers

Eiman Alnuaimi

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Tags: Computer science, Heterogeneous systems, HPC, Intel, Intel Data Center GPU Max 1550, LLM, MPI, nVidia, nVidia GH200, nVidia V100, Optimization, Package, performance portability, Thesis

June 8, 2025 by hgpu

A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading

Mohammad Atif, Tianle Wang, Zhihua Dong, Charles Leggett, Meifeng Lin

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Tags: Benchmarking, Computer science, Heterogeneous systems, nVidia A100, nVidia RTX A6000, nVidia V100, OpenMP, Package

March 10, 2025 by hgpu

On the Partitioning of GPU Power among Multi-Instances

Tirth Vamja, Kaustabha Ray, Felix George, UmaMaheswari C Devi

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Tags: Computer science, CUDA, Energy-efficient computing, Machine learning, Matrix multiplication, nVidia, nVidia A100, nVidia V100, Performance

February 3, 2025 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

Naifeng Zhang, Franz Franchetti

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Tags: Code generation, Computer science, CUDA, Linear Algebra, Modular arithmetic, nVidia, nVidia GeForce RTX 4090, nVidia H100, nVidia V100, Package, Security

January 20, 2025 by hgpu

Leveraging the potential of task-based programming with OpenMP task graphs

Chenle Yu

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Tags: Computer science, CUDA, nVidia, nVidia V100, OpenMP, Package, Thesis

December 15, 2024 by hgpu

A Distributed-memory Tridiagonal Solver Based on a Specialised Data Structure Optimised for CPU and GPU Architectures

Semih Akkurt, Sébastien Lemaire, Paul Bartholomew, Sylvain Laizet

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia A100, nVidia GH200, nVidia H100, nVidia V100, OpenMP, PDEs

November 24, 2024 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

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

LC Framework

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

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

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high performance computing on graphics processing units: hgpu.org

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

Tutoring LLM into a Better CUDA Optimizer

BePilot: An AI Programming Assistant for Compiler Backend Development

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

LiteGD: Lightweight and dynamic GPU Dispatching for Large-scale Heterogeneous Clusters

Acceleration as a Service (XaaS) Source Containers

A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading

On the Partitioning of GPU Power among Multi-Instances

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

Leveraging the potential of task-based programming with OpenMP task graphs

A Distributed-memory Tridiagonal Solver Based on a Specialised Data Structure Optimised for CPU and GPU Architectures

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

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

LC Framework

pplx-garden: Perplexity open source garden for inference technology

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