Algorithms | Page 55

Programming

hgpu.org » Programming » Algorithms

Different Optimization Strategies and Performance Evaluation of Reduction on Multicore CUDA Architecture

Chhaya Patel

View

Download (PDF)

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

January 30, 2015 by hgpu

Accelerate micromagnetic simulations with GPU programming in MATLAB

Ru Zhu

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 650 Ti, Package

January 30, 2015 by hgpu

Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

Jan Verschelde, Xiangcheng Yu

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Extended precision, Linear Algebra, Mathematical Software, Numerical Analysis, nVidia, Package, Tesla K20

January 28, 2015 by hgpu

Performance Analysis of Join Algorithms on GPUs

Ran Rui, Hao Li, Yi-Cheng Tu

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Databases, Join, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, Performance

January 26, 2015 by hgpu

Real-time physically cloth simulation with CUDA

Li Huaming, Kang Baosheng

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, OpenGL, Rendering

January 23, 2015 by hgpu

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Ana Lucia Varbanescu, Merijn Verstraaten, Cees de Laat, Ate Penders, Alexandru Iosup, Henk Sips

View

Download (PDF)

Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C2050

January 23, 2015 by hgpu

Reproducible and Accurate Matrix Multiplication for GPU Accelerators

Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Matrix multiplication, nVidia, OpenCL, Performance, Tesla K20

January 21, 2015 by hgpu

Hybrid Multicore Algorithms for Some Semi-Numerical Applications and Graphs

Dip Sankar Banerjee

View

Download (PDF)

Tags: Algorithms, Cell processor, Computer science, CUDA, Distributed computing, List ranking, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, OpenCL, Sorting, Thesis

January 19, 2015 by hgpu

SW#db: GPU-accelerated exact sequence similarity database search

Matija Korpar, Martin Sosic, Dino Blazeka, Mile Sikic

View

Download (PDF)

Source codes

Tags: Algorithms, Biology, CUDA, Databases, Next-Generation sequencing, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX 780, Package, Smith-Waterman algorithm

January 16, 2015 by hgpu

Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units

Amlan Chatterjee

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Sorting, Tesla K20, Thesis

January 16, 2015 by hgpu

GPU Processing for UAS-Based LFM-CW Stripmap SAR

Craig Stringham, David G. Long

View

Download (PDF)

Tags: Algorithms, CUDA, Image processing, Motion compensation, nVidia, nVidia GeForce GTX 285, SAR

January 16, 2015 by hgpu

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Mahmut Murat Gocmen

View

Download (PDF)

Source codes

Tags: Algorithms, CUBLAS, CUDA, FEM, Finite element method, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 280, Package, Tesla C2075, Thesis

January 16, 2015 by hgpu

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

ThunderKittens: Tile primitives for speedy kernels

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

NVIDIA Nemotron Parse 1.1

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

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Different Optimization Strategies and Performance Evaluation of Reduction on Multicore CUDA Architecture

Accelerate micromagnetic simulations with GPU programming in MATLAB

Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

Performance Analysis of Join Algorithms on GPUs

Real-time physically cloth simulation with CUDA

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Reproducible and Accurate Matrix Multiplication for GPU Accelerators

SW#db: GPU-accelerated exact sequence similarity database search

Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units

GPU Processing for UAS-Based LFM-CW Stripmap SAR

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Recent source codes

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

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

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

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

Most viewed papers (last 30 days)