high performance computing on graphics processing units: hgpu.org

Applications

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High Performance GPU Implementation of KNN Algorithm: A Review

Pooja Bidye, Pradnya Borkar, Nitin Rakesh

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Tags: Computer science, Machine learning, Nearest neighbour, nVidia, Review

September 21, 2025 by hgpu

Dato: A Task-Based Programming Model for Dataflow Accelerators

Shihan Fang, Hongzheng Chen, Niansong Zhang, Jiajie Li, Han Meng, Adrian Liu, Zhiru Zhang

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Tags: Computer science, FPGA, nVidia, Package, Programming Languages, Python

September 21, 2025 by hgpu

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

Robert Tjarko Lange, Qi Sun, Aaditya Prasad, Maxence Faldor, Yujin Tang, David Ha

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Tags: Benchmarking, Computer science, CUDA, Filtering, LLM, nVidia, nVidia H100, Package, Software Engineering

September 21, 2025 by hgpu

Evolution of Kernels: Automated RISC-V Kernel Optimization with Large Language Models

Siyuan Chen, Zhichao Lu, Qingfu Zhang

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Tags: Computer science, CUDA, LLM, nVidia, Software Engineering

September 21, 2025 by hgpu

An HPC Benchmark Survey and Taxonomy for Characterization

Andreas Herten, Olga Pearce, Filipe S. M. Guimarães

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Tags: Benchmarking, Computer science, CUDA, Fortran, HIP, HPC, MPI, OpenACC, OpenCL, OpenMP, Package, Performance, ROCm, SYCL

September 14, 2025 by hgpu

Towards Calculating HPC CUDA Kernel Performance on Nvidia GPUs

Dumeni Manatschal

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce RTX 3080, Performance, PTX, Thesis

September 14, 2025 by hgpu

Home-made Diffusion Model from Scratch to Hatch

Shih-Ying Yeh

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce RTX 5090, Package, Python, PyTorch

September 14, 2025 by hgpu

High Performance Matrix Multiplication

Ethan Davis

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Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, OpenMP, Package, Performance, Python, Tesla V100

September 14, 2025 by hgpu

Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software

Siddharth Samsi, Dan Campbell, Emanuel Scoullos, Oded Green

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, nVidia A100, nVidia H100, nVidia H200, Sensing

September 14, 2025 by hgpu

CrossTL: A Universal Programming Language Translator with Unified Intermediate Representation

Nripesh Niketan, Vaatsalya Shrivastva

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Tags: Compilers, Computer science, CUDA, DirectX, GLSL, HIP, HLSL, nVidia, OpenGL, Package, Programming Languages, Vulkan

September 7, 2025 by hgpu

GPU-acceleration of the Discontinuous Galerkin Shallow Water Equations Solver (DG-SWEM) using CUDA and OpenACC

Chayanon Wichitrnithed, Eirik Valseth, Clint Dawson

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Tags: cfd, Computational Physics, CUDA, Data parallelism, Fluid dynamics, Fortran, MPI, nVidia, nVidia GH200, OpenACC, Package, Physics

September 7, 2025 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

High Performance GPU Implementation of KNN Algorithm: A Review

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

Evolution of Kernels: Automated RISC-V Kernel Optimization with Large Language Models

An HPC Benchmark Survey and Taxonomy for Characterization

Towards Calculating HPC CUDA Kernel Performance on Nvidia GPUs

Home-made Diffusion Model from Scratch to Hatch

High Performance Matrix Multiplication

Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software

CrossTL: A Universal Programming Language Translator with Unified Intermediate Representation

GPU-acceleration of the Discontinuous Galerkin Shallow Water Equations Solver (DG-SWEM) using CUDA and OpenACC

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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