high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce G 110 M

Parallel Particle Swarm Optimization for Image Segmentation

Agustinus Kristiadi, Pranowo Pranowo, Paulus Mudjihartono

View

Tags: Clustering, CUDA, Image processing, nVidia, nVidia GeForce G 110 M, Particle swarm optimization

March 14, 2013 by hgpu

* * *

E2C-Sim: a simulator and workload generator for Edge-to-Cloud environments

E2C: A Visual Simulator to Reinforce Education of Heterogeneous Computing Systems

Kernel Tuner

Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications

Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

See all packages

* * *

* * *

HGPU group © 2010-2023 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: