high performance computing on graphics processing units: hgpu.org

Changxin Ke, Rui Zhang, Shuo Wang, Li Ding, Guangli Li, Yuanbo Wen, Shuoming Zhang, Ruiyuan Xu, Jin Qin, Jiaming Guo, Chenxi Wang, Ling Li, Qi Guo, Yunji Chen

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Tags: Code generation, Computer science, CUDA, HPC, LLM, Machine learning, nVidia, nVidia A100, nVidia GeForce RTX 4090, Package

July 13, 2025 by hgpu

Demystifying NCCL: An In-depth Analysis of GPU Communication Protocols and Algorithms

Zhiyi Hu, Siyuan Shen, Tommaso Bonato, Sylvain Jeaugey, Cedell Alexander, Eric Spada, Jeff Hammond, Torsten Hoefler

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Tags: Computer science, CUDA, GPU cluster, Network communication, nVidia, nVidia GH200

July 13, 2025 by hgpu

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Joshua Bakita, James H. Anderson

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Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 4090, nVidia RTX 6000 Ada, Package, Task scheduling

July 13, 2025 by hgpu

Efficient GPU Implementation of Multi-Precision Integer Division

Aske N. Raahauge, Martin B. Marchioro, Marc I. Løvenskjold

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Tags: Computer science, CUDA, Extended precision, Futhark, nVidia, nVidia A100, Package, Thesis

July 6, 2025 by hgpu

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

Joshua H. Davis, Daniel Nichols, Ishan Khillan, Abhinav Bhatele

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Tags: Benchmarking, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenMP, Package

July 6, 2025 by hgpu

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

Jinliang Shi, Shigang Li, Youxuan Xu, Xueying Wang, Rongtian Fu, Zhi Ma, Tong Wu

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce RTX 4090, nVidia H100, Package, Sparse matrix

July 6, 2025 by hgpu

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

Weiyi Xia, Maxim Moraru, Ying Wai Li, Timothy Liao, James R. Chelikowsky, Cai-Zhuang Wang

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Tags: Anisotropy, Computational Physics, Condensed matter, CUDA, Machine learning, Materials Science, Neural networks, nVidia, nVidia A100, Package, Physics

July 6, 2025 by hgpu

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

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

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

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high performance computing on graphics processing units: hgpu.org

Performance Portable Gradient Computations Using Source Transformation

Kevin: Multi-Turn RL for Generating CUDA Kernels

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

Pre-Training LLMs on a budget: A comparison of three optimizers

Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Demystifying NCCL: An In-depth Analysis of GPU Communication Protocols and Algorithms

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

Recent source codes

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

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