Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 161 tok/s
Gemini 2.5 Pro 52 tok/s Pro
GPT-5 Medium 32 tok/s Pro
GPT-5 High 33 tok/s Pro
GPT-4o 108 tok/s Pro
Kimi K2 207 tok/s Pro
GPT OSS 120B 471 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Particle-based and Meshless Methods with Aboria (1704.08907v2)

Published 28 Apr 2017 in cs.MS, cond-mat.soft, and q-bio.QM

Abstract: Aboria is a powerful and flexible C++ library for the implementation of particle-based numerical methods. The particles in such methods can represent actual particles (e.g. Molecular Dynamics) or abstract particles used to discretise a continuous function over a domain (e.g. Radial Basis Functions). Aboria provides a particle container, compatible with the Standard Template Library, spatial search data structures, and a Domain Specific Language to specify non-linear operators on the particle set. This paper gives an overview of Aboria's design, an example of use, and a performance benchmark.

Citations (11)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.