high performance computing on graphics processing units: hgpu.org

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Harnessing Batched BLAS/LAPACK Kernels on GPUs for Parallel Solutions of Block Tridiagonal Systems

David Jin, Alexis Montoison, Sungho Shin

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Tags: AMD Radeon Instinct MI300X, ATI, Benchmarking, BLAS, Computer science, CUDA, Factorization, Julia, nVidia, nVidia H200, Package, ROCm

September 7, 2025 by hgpu

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Jacob Wahlgren, Gabin Schieffer, Ruimin Shi, Edgar A. León, Roger Pearce, Maya Gokhale, Ivy Peng

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Tags: AMD Radeon Instinct MI300A, ATI, Benchmarking, Computer science, HIP, Memory model, Package

August 31, 2025 by hgpu

Scaling GPU-Accelerated Databases beyond GPU Memory Size

Yinan Li, Bailu Ding, Ziyun Wei, Lukas Maas, Momin Al-Ghosien, Spyros Blanas, Nicolas Bruno, Carlo Curino, Matteo Interlandi, Craig Peeper, Kaushik Rajan, Surajit Chaudhuri, Johannes Gehrke

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Tags: Benchmarking, Computer science, Databases, Memory, nVidia, nVidia A100, nVidia H100

August 31, 2025 by hgpu

Inter-APU Communication on AMD MI300A Systems via Infinity Fabric: a Deep Dive

Gabin Schieffer, Jacob Wahlgren, Ruimin Shi, Edgar A. León, Roger Pearce, Maya Gokhale, Ivy Peng

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300A, APU, ATI, Benchmarking, Computer science, HIP, HPC, MPI, Performance

August 24, 2025 by hgpu

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

Jianghui Wang, Vinay Joshi, Saptarshi Majumder, Xu Chao, Bin Ding, Ziqiong Liu, Pratik Prabhanjan Brahma, Dong Li, Zicheng Liu, Emad Barsoum

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Tags: AMD Radeon Instinct MI300X, ATI, Benchmarking, Code generation, Computer science, Deep learning, Package, Python, ROCm, Triton

August 3, 2025 by hgpu

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Juan José Ropero, Manuel de Castro, Diego R. Llanos

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Tags: AMD FirePro W7800, ATI, Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia RTX 4500 Ada, OpenCL, Package

August 3, 2025 by hgpu

Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks

Aaron Jarmusch, Nathan Graddon, Sunita Chandrasekaran

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, nVidia GeForce RTX 5080, nVidia H100, Performance, PTX

July 20, 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

Omniwise: Predicting GPU Kernels Performance with LLMs

Zixian Wang, Cole Ramos, Muhammad A. Awad, Keith Lowery

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Tags: AMD, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, Artificial intelligence, Benchmarking, Computer science, LLM, Neural networks, Performance, ROCm

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

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

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Jiaqi Lv, Xufeng He, Yanchen Liu, Xu Dai, Yang Hu, Shouyi Yin

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Tags: AI, Benchmarking, Compilers, Computer science, CUDA, Deep learning, LLM, nVidia, nVidia A100, Package, performance portability

June 15, 2025 by hgpu

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

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high performance computing on graphics processing units: hgpu.org

Harnessing Batched BLAS/LAPACK Kernels on GPUs for Parallel Solutions of Block Tridiagonal Systems

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Scaling GPU-Accelerated Databases beyond GPU Memory Size

Inter-APU Communication on AMD MI300A Systems via Infinity Fabric: a Deep Dive

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks

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

Omniwise: Predicting GPU Kernels Performance with LLMs

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

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Recent source codes

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

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