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PEAK: A Performance Engineering AI-Assistant for GPU Kernels Powered by Natural Language Transformations

Muhammad Usman Tariq, Abhinav Jangda, Angelica Moreira, Madan Musuvathi, Tyler Sorensen

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Tags: AI, AMD, AMD Radeon Instinct MI200, ATI, Computer science, CUDA, HIP, HLSL, LLM, NLP, nVidia, nVidia RTX A6000

December 29, 2025 by hgpu

Chopper: A Multi-Level GPU Characterization Tool & Derived Insights Into LLM Training Inefficiency

Marco Kurzynski, Shaizeen Aga, Di Wu

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Tags: AMD, AMD Radeon Instinct MI300X, ATI, Benchmarking, Computer science, Data parallelism, LLM, ROCm

December 15, 2025 by hgpu

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

Ryan Swann, Muhammad Osama, Xiaohu Guo, Bryant Nelson, Lixun Zhang, Alex Brown, Yen Ong, Ali Yazdani, Sean Siddens, Ganesh Dasika, Alex Underwood

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Tags: AMD, AMD Radeon Instinct MI300X, AMD Radeon Instinct MI350X, ATI, BLAS, Computer science, HPC, Package, Performance, ROCm, Triton

December 7, 2025 by hgpu

A Compute Graph Simulation and Implementation Framework Targeting AMD Versal AI Engines

Jonathan Strobl, Leonardo Solis-Vasquez, Yannick Lavan, Andreas Koch

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Tags: AI, AMD, Code generation, Computer science, FPGA

October 26, 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

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

Timothée David--Cléris, Guillaume Laibe, Yona Lapeyre

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Tags: AMD, AMD Radeon Instinct MI250X, Astrophysics, CUDA, MPI, nVidia, nVidia A100, OpenMP, Package, Physics, PTX, ROCm, SYCL

March 23, 2025 by hgpu

Seamless acceleration of Fortran intrinsics via AMD AI engines

Nick Brown, Gabriel Rodríguez Canal

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Tags: AI, AMD, Computer science, Fortran, Linear Algebra, Package, Performance

February 24, 2025 by hgpu

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Sanil Rao, Mike Franusich, , Mohammad Alaul Haque Monil, Het Mankad, Jeffrey S. Vetter, Franz Franchetti

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Tags: AMD, ATI, Code generation, Computer science, CUDA, Differential equations, Fortran, Heterogeneous systems, HIP, nVidia, OpenCL, OpenMP, Partial differential equations, PDEs

December 8, 2024 by hgpu

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Gabin Schieffer, Ruimin Shi, Stefano Markidis, Andreas Herten, Jennifer Faj, Ivy Peng

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Tags: AMD, AMD Radeon Instinct MI250X, ATI, Computer science, HIP, Machine learning, Memory, Performance

October 6, 2024 by hgpu

Portable high-order finite element kernels I: Streaming Operations

Noel Chalmers, Tim Warburton

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Tags: AMD, AMD Radeon Instinct MI60, AMD Radeon VII, Computer science, CUDA, FEM, HIP, Mathematical Software, nVidia, nVidia GeForce GTX Titan V, OCCA, Portability, Tesla V100

October 18, 2020 by hgpu

Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs

Cade Brown, Ahmad Abdelfattah, Stanimire Tomov, Jack Dongarra

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Tags: AMD, AMD Radeon Instinct MI25, AMD Radeon Instinct Mi50, Benchmarking, Computer science, Heterogeneous systems, HIP, HPC, Linear Algebra, Performance, Portability

August 23, 2020 by hgpu

Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Nuno Fachada, Agostinho C. Rosa

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Tags: Agent-based modeling, AMD, cpu, Intel, OpenCL, simulation

July 24, 2019 by fakenmc

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

PEAK: A Performance Engineering AI-Assistant for GPU Kernels Powered by Natural Language Transformations

Chopper: A Multi-Level GPU Characterization Tool & Derived Insights Into LLM Training Inefficiency

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

A Compute Graph Simulation and Implementation Framework Targeting AMD Versal AI Engines

Omniwise: Predicting GPU Kernels Performance with LLMs

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

Seamless acceleration of Fortran intrinsics via AMD AI engines

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Portable high-order finite element kernels I: Streaming Operations

Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs

Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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