high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

High Performance Multi-agent System based Simulations

Prashant Sethia

View

Download (PDF)

Source codes

Tags: Algorithms, Cloud, Computer science, CUDA, Distributed computing, MapReduce, nVidia, Package, Tesla T10

December 8, 2011 by hgpu

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Pramod Kumbhar

View

Download (PDF)

Tags: ATI, ATI FireStream, Computer science, CUDA, Differential equations, GPU cluster, nVidia, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Thesis

December 8, 2011 by hgpu

High performance dense linear system solver with soft error resilience

Peng Du, Piotr Luszczek, Jack Dongarra

View

Download (PDF)

Tags: Algorithms, Computer science, Factorization, Linear Algebra

December 8, 2011 by hgpu

Speeding up the evaluation phase of GP classification algorithms on GPUs

Alberto Cano, Amelia Zafra, Sebastian Ventura

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package

December 8, 2011 by hgpu

An Algorithm for Detecting Cycles in Undirected Graphs using CUDA Technology

Maytham Safar, Fahad Mahdi, Khaled Mahdi

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce 9500 GS

December 8, 2011 by hgpu

Evolving Neural Networks on GPUs

Johannes Hofmann

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Finance, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla C1060

December 7, 2011 by hgpu

GPU Implementation of the Keccak Hash Function Family

Pierre-Louis Cayrel, Gerhard Hoffmann, Michael Schneider

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 295, Package, Security, Tesla C2050

December 7, 2011 by hgpu

Parallelizing AES on multicores and GPUs

Julian Ortega, Helmuth Trefftz, Christian Trefftz

View

Download (PDF)

Tags: AES, Algorithms, Block Ciphers, Computer science, CUDA, nVidia, nVidia GeForce GT 330 M, nVidia Quadro FX 1800, OpenMP, Security

December 7, 2011 by hgpu

Sparse-Matrix-CG-Solver in CUDA

Dominik Michels

View

Download (PDF)

Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 480, Sparse matrix

December 7, 2011 by hgpu

Accelerating Braided B+ Tree Searches on a GPU with CUDA

Jordan Fix, Andrew Wilkes, Kevin Skadron

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480

December 7, 2011 by hgpu

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Petr Pospichal

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, nVidia, nVidia GeForce GTX 480, Performance

December 7, 2011 by hgpu

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

Jan Fousek, Jiri Filipovic, Matus Madzin

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

December 6, 2011 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

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

High performance dense linear system solver with soft error resilience

Speeding up the evaluation phase of GP classification algorithms on GPUs

An Algorithm for Detecting Cycles in Undirected Graphs using CUDA Technology

Evolving Neural Networks on GPUs

GPU Implementation of the Keccak Hash Function Family

Parallelizing AES on multicores and GPUs

Sparse-Matrix-CG-Solver in CUDA

Accelerating Braided B+ Tree Searches on a GPU with CUDA

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

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

Most viewed papers (last 30 days)