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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

WiLLM: An Open Wireless LLM Communication System

Boyi Liu, Yongguang Lu, Jianguo Zhao, Qiang Yang, Wen Wu, Lin Chen, Jagmohan Chauhan, Jun Zhang

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Tags: Computer science, LLM, Network communications, nVidia, nVidia GeForce RTX 4090, Package

June 29, 2025 by hgpu

GCStack+GCScaler: Fast and Accurate GPU Performance Analyses Using Fine-Grained Stall Cycle Accounting and Interval Analysis

Hanna Cha, Sungchul Lee, Jounghoo Lee, Yeonan Ha, Joonsung Kim, Youngsok Kim

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Tags: Benchmarking, Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce RTX 3070, Performance

June 29, 2025 by hgpu

No More Shading Languages: Compiling C++ to Vulkan Shaders

H. Devillers, M. Kurtenacker, R. Membarth, S. Lemme, M. Kenzel, Ö. Yazici, P. Slusallek

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Tags: 3D Graphics and Realism, AMD Radeon RX 7900 XT, ATI, Compilers, GLSL, nVidia, nVidia GeForce RTX 3050 Ti, nVidia GeForce RTX 4070, Package, Raytracing, Rendering, Vulkan

June 29, 2025 by hgpu

A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

Hossein Albakri, Kazem Cheshmi

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Tags: Compilers, Computer science, CUBLAS, CUDA, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia A100, Programming Languages, Sparse matrix

June 22, 2025 by hgpu

Engineering Supercomputing Platforms for Biomolecular Applications

Robert Welch, Charles Laughton, Oliver Henrich, Tom Burnley, Daniel Cole, Alan Real, Sarah Harris, James Gebbie-Rayet

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct MI300X, ATI, Benchmarking, Biology, Biomolecules, Computational biology, CUDA, HPC, Molecular dynamics, nVidia, nVidia A100, nVidia GH200, nVidia H100, Package, Physics, ROCm, Tesla V100

June 22, 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

CUDA-LLM: LLMs Can Write Efficient CUDA Kernels

Wentao Chen, Jiace Zhu, Qi Fan, Yehan Ma, An Zou

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Tags: Artificial intelligence, Code generation, Computer sceince, CUDA, LLM, nVidia, nVidia GeForce GTX 1660, nVidia GeForce RTX 3090 Ti

June 15, 2025 by hgpu

Introduction to Computer Vision

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

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high performance computing on graphics processing units: hgpu.org

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

WiLLM: An Open Wireless LLM Communication System

GCStack+GCScaler: Fast and Accurate GPU Performance Analyses Using Fine-Grained Stall Cycle Accounting and Interval Analysis

No More Shading Languages: Compiling C++ to Vulkan Shaders

A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

Engineering Supercomputing Platforms for Biomolecular Applications

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

CUDA-LLM: LLMs Can Write Efficient CUDA Kernels

Recent source codes

Introduction to Computer Vision

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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