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Stencil Computation at the Intersection of AI and HPC

Timothee Ewart, Mauricio Araya-Polo

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Tags: AI, AMD, AMD Radeon Instinct MI325X, Computer science, HPC, Intel Arc B580, Intel B70, Intel Data Center GPU Max 1550, nVidia, nVidia A100, nVidia H100, nVidia RTX PRO 6000, performance portability, Stencil computation, SYCL, Triton

September 14, 2026 by hgpu

Taming Bitwise Behavior in GPU Kernels with Tensor Core: Black-Box Reconstruction, Compiler Enforcement, and Static Verification

Ziteng Yang, Nicholas J. Riasanovsky, Warren Deng, Vivek Sarkar

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Tags: Computer science, CUBLAS, CUDA, nVidia, nVidia GB300, nVidia H100, PTX, Triton

September 14, 2026 by hgpu

Concurrency Response of Plain Global Loads on the NVIDIA H100

Somashekar Manjunath, Rahul Ramachandra M

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, nVidia H100, Performance

August 30, 2026 by hgpu

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

Genghan Zhang, Yixin Dong, Chengze Fan, Zhichen Zeng, Yueming Yuan, Shaowei Zhu, Kunle Olukotun

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Tags: Benchmarking, Computer science, LLM, nVidia, nVidia B200, nVidia H100, Package, PTX

August 30, 2026 by hgpu

An HPC Approach to Accelerate Tensor Decompositions

Markus Hellgren, Erna Begovic Kovac, Hans O. Karlsson, Roman Iakymchuk

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Tags: Computer science, CUDA, HPC, nVidia, nVidia H100

August 30, 2026 by hgpu

Validation-Centric AI-Assisted GPU Porting of a 250,000+ Line Legacy Weather Simulation Code

Tetsuya Hoshino, Masaya Kato, Kazuhisa Tsuboki, Daichi Mukunoki, Takahiro Katagiri, Toshihiro Hanawa

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Tags: AI, Code generation, Computer science, Fortran, MPI, nVidia, nVidia GH200, nVidia H100, OpenACC, OpenMP

August 17, 2026 by hgpu

Enhancing the Performance Analysis of NCCL GPU Collectives

Jurij Cerar

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Tags: Computer science, CUDA, nVidia, nVidia H100, Performance, Tesla T4, Thesis

July 13, 2026 by hgpu

The Correctness Illusion in LLM-Generated GPU Kernels

Dipankar Sarkar

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Tags: Benchmarking, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A10, nVidia A100, nVidia GeForce RTX 3060, nVidia H100, nVidia L40s, Triton

June 28, 2026 by hgpu

Leveraging AI Ecosystem for Portable and Sustainable GPU Kernels in HPC

Yanbo Zhao, Zhaonan Meng, Sai Krishna Teja Varma Manthena, Xu Liu, Ajay Panyala, Jiajia Li

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Tags: AMD, AMD Radeon Instinct MI300X, Computer science, DSL, HPC, nVidia, nVidia GeForce RTX 4090, nVidia H100, PTX, Python, ROCm, Triton

June 17, 2026 by hgpu

KEET: Explaining Performance of GPU Kernels Using LLM Agents

Joshua H. Davis, Klaudiusz Rydzy, Srinivasan Ramesh, Aadit Nilay, Daniel Nichols, Swapna Raj, Nikhil Jain, Abhinav Bhatele

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Tags: Computer science, CUDA, LLM, nVidia, nVidia H100, Performance

May 11, 2026 by hgpu

CuBridge: An LLM-Based Framework for Understanding and Reconstructing High-Performance Attention Kernels

Xing Ma, Yangjie Zhou, Wu Sun, Zihan Liu, Jingwen Leng, Yun Lin, Shixuan Sun, Minyi Guo, Jin Song Dong

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Tags: Computer science, CUDA, Deep learning, LLM, nVidia, nVidia A100, nVidia H100

May 11, 2026 by hgpu

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Divakar Kumar Yadav, Tian Zhao, Deepak Kumar

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Tags: Computer science, CUBLAS, CUDA, LLM, nVidia, nVidia B200, nVidia H100, nVidia RTX PRO 6000, Package, Performance, Triton

May 3, 2026 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

Stencil Computation at the Intersection of AI and HPC

Taming Bitwise Behavior in GPU Kernels with Tensor Core: Black-Box Reconstruction, Compiler Enforcement, and Static Verification

Concurrency Response of Plain Global Loads on the NVIDIA H100

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

An HPC Approach to Accelerate Tensor Decompositions

Validation-Centric AI-Assisted GPU Porting of a 250,000+ Line Legacy Weather Simulation Code

Enhancing the Performance Analysis of NCCL GPU Collectives

The Correctness Illusion in LLM-Generated GPU Kernels

Leveraging AI Ecosystem for Portable and Sustainable GPU Kernels in HPC

KEET: Explaining Performance of GPU Kernels Using LLM Agents

CuBridge: An LLM-Based Framework for Understanding and Reconstructing High-Performance Attention Kernels

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Recent source codes

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

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