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Survey of HPC in US Research Institutions

Peng Shu, Junhao Chen, Zhengliang Liu, Huaqin Zhao, Xinliang Li, Tianming Liu

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Tags: AI, Computer science, HPC, survey

June 29, 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

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

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

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

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

A CPU+FPGA OpenCL Heterogeneous Computing Platform for Multi-Kernel Pipeline

Yuefei Wang, Wendong Mao, Lang Feng, Jin Sha, Zhongfeng Wang

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL

June 22, 2025 by hgpu

A First Look at Bugs in LLM Inference Engines

Mugeng Liu, Siqi Zhong, Weichen Bi, Yixuan Zhang, Zhiyang Chen, Zhenpeng Chen, Xuanzhe Liu, Yun Ma

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Tags: AI, Computer science, LLM, Software Engineering

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

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

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

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

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Applications

Survey of HPC in US Research Institutions

Omniwise: Predicting GPU Kernels Performance with LLMs

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

WiLLM: An Open Wireless LLM Communication System

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

A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

A CPU+FPGA OpenCL Heterogeneous Computing Platform for Multi-Kernel Pipeline

A First Look at Bugs in LLM Inference Engines

Engineering Supercomputing Platforms for Biomolecular Applications

CUDA-LLM: LLMs Can Write Efficient CUDA Kernels

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

Recent source codes

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

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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