high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

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

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

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

Managing Multi Instance GPUs for High Throughput and Energy Savings

Abhijeet Saraha, Yuanbo Li, Chris Porter, Santosh Pande

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Tags: Computer science, CUDA, Energy-efficient computing, LLM, nVidia, nVidia A100, PyTorch, Security

September 7, 2025 by hgpu

Profiling Concurrent Vision Inference Workloads on NVIDIA Jetson – Extended

Abhinaba Chakraborty, Wouter Tavernier, Akis Kourtis, Mario Pickavet, Andreas Oikonomakis, Didier Colle

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Tags: Computer science, CUDA, nVidia, nVidia Jetson Nano, nVidia Jetson Orin Nano, Performance

August 24, 2025 by hgpu

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Jiarong Xing, Yifan Qiao, Simon Mo, Xingqi Cui, Gur-Eyal Sela, Yang Zhou, Joseph Gonzalez, Ion Stoica

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Tags: Computer science, CUDA, LLM, nVidia, nVidia A100, Package, Performance, PyTorch

August 24, 2025 by hgpu

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Ryan R. Curtin, Marcus Edel, Conrad Sanderson

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Programming techniques

August 24, 2025 by hgpu

Fuzz4cuda: Fuzzing Your Nvidia Gpu Libraries Through Debug Interface

Yuhao Zhou, Peng Jia, Jiayong Liu, Ximing Fan

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Tags: Computer science, CUDA, nVidia, nVidia RTX A6000, PTX, Security

August 24, 2025 by hgpu

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

Oscar Amoros, Albert Andaluz, Johnny Nunez, Antonio J. Pena

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Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 4090, Package, Performance

August 17, 2025 by hgpu

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision

Evelyne Ringoot, Rabab Alomairy, Valentin Churavy, Alan Edelman

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Tags: AMD Radeon Instinct MI250, Apple M1 Pro, ATI, Computer science, HIP, Intel, Intel Ponte Vecchio Max 1100, Kokkos, Linear Algebra, Machine learning, nVidia, nVidia A100, nVidia GeForce RTX 4060, nVidia H100, OpenCL, SYCL

August 17, 2025 by hgpu

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Chris S. Lin, Joyce Qu, Gururaj Saileshwar

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia RTX A6000, Package, Security

August 17, 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

Programming

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

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

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

Managing Multi Instance GPUs for High Throughput and Energy Savings

Profiling Concurrent Vision Inference Workloads on NVIDIA Jetson – Extended

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Fuzz4cuda: Fuzzing Your Nvidia Gpu Libraries Through Debug Interface

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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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