high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Performance Analysis of an Astrophysical Simulation Code on the Intel Xeon Phi Architecture

Vahid Noormofidi, Susan R. Atlas, Huaiyu Duan

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Tags: Astrophysics, Computer science, Intel Xeon Phi, MPI, OpenMP, Performance

October 11, 2015 by hgpu

GPU Accelarated Multi-Block Lattice Boltzmann Solver for Viscous Flow Problems

Gregorio Gerardo Spinelli, Bayram Celik

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia

October 11, 2015 by hgpu

Accelerating the D3Q19 Lattice Boltzmann Model with OpenACC and MPI

Alessandro Gabbana

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Tags: Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, MPI, nVidia, OpenACC, Tesla K80, Thesis

October 11, 2015 by hgpu

GPU acceleration of preconditioned solvers for ill-conditioned linear systems

Rohit Gupta

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Tags: Computer science, Conjugate gradient solver, MPI, nVidia, Tesla C2070, Thesis

October 11, 2015 by hgpu

Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit

Felix Weninger, Johannes Bergmann, Bjorn Schuller

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Tags: Benchmarking, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 560, Package, Speech recognition

October 8, 2015 by hgpu

GPU-Based Computation of 2D Least Median of Squares with Applications to Fast and Robust Line Detection

Gil Shapira, Tal Hassner

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 720, Package

October 8, 2015 by hgpu

Solving the Quadratic Assignment Problem on heterogeneous environment (CPUs and GPUs) with the application of Level 2 Reformulation and Linearization Technique

Alexandre Domingues Goncalves, Artur Alves Pessoa, Lucia Maria de Assumpcao Drummond, Cristiana Bentes, Ricardo Farias

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, Tesla C2070

October 8, 2015 by hgpu

Exploiting Task-Parallelism on GPU Clusters via OmpSs and rCUDA Virtualization

Adrian Castello, Rafael Mayo, Judit Planas, Enrique S. Quintana-Orti

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Tags: Computer science, CUDA, GPU cluster, nVidia, OmpSs, Tesla C2050, Tesla M2050, Virtualization

October 8, 2015 by hgpu

Kinematic Modelling of Disc Galaxies using Graphics Processing Units

Georgios Bekiaris, Karl Glazebrook, Christopher J. Fluke, Roberto Abraham

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Tags: Algorithms, Astrophysics, CUDA, nVidia, Package, Tesla C2070, Tesla K40

October 8, 2015 by hgpu

Parallel Graph Algorithms on the Xeon Phi Coprocessor

Dennis Felsing

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Tags: Algorithms, Computer science, Graph theory, Intel Xeon Phi, OpenMP, Thesis, Visualization

October 6, 2015 by hgpu

Optimizing GPU-accelerated Group-By and Aggregation

Tomas Karnagel, Rene Mueller, Guy M. Lohman

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX Titan

October 6, 2015 by hgpu

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Rahul Garg

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Tags: AMD Radeon HD 8650, ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Computer science, Intel HD Graphics 4000, Matlab, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Package, Python, Tesla C2050, Thesis

October 6, 2015 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

Performance Analysis of an Astrophysical Simulation Code on the Intel Xeon Phi Architecture

GPU Accelarated Multi-Block Lattice Boltzmann Solver for Viscous Flow Problems

Accelerating the D3Q19 Lattice Boltzmann Model with OpenACC and MPI

GPU acceleration of preconditioned solvers for ill-conditioned linear systems

Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit

GPU-Based Computation of 2D Least Median of Squares with Applications to Fast and Robust Line Detection

Solving the Quadratic Assignment Problem on heterogeneous environment (CPUs and GPUs) with the application of Level 2 Reformulation and Linearization Technique

Exploiting Task-Parallelism on GPU Clusters via OmpSs and rCUDA Virtualization

Kinematic Modelling of Disc Galaxies using Graphics Processing Units

Parallel Graph Algorithms on the Xeon Phi Coprocessor

Optimizing GPU-accelerated Group-By and Aggregation

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

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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