Papers
Topics
Authors
Recent
AI Research 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 74 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 13 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 87 tok/s Pro
Kimi K2 98 tok/s Pro
GPT OSS 120B 464 tok/s Pro
Claude Sonnet 4 40 tok/s Pro
2000 character limit reached

Efficiency of linked cell algorithms (1006.1239v1)

Published 7 Jun 2010 in physics.comp-ph, cond-mat.mtrl-sci, and cond-mat.soft

Abstract: The linked cell list algorithm is an essential part of molecular simulation software, both molecular dynamics and Monte Carlo. Though it scales linearly with the number of particles, there has been a constant interest in increasing its efficiency, because a large part of CPU time is spent to identify the interacting particles. Several recent publications proposed improvements to the algorithm and investigated their efficiency by applying them to particular setups. In this publication we develop a general method to evaluate the efficiency of these algorithms, which is mostly independent of the parameters of the simulation, and test it for a number of linked cell list algorithms. We also propose a combination of linked cell reordering and interaction sorting that shows a good efficiency for a broad range of simulation setups.

Citations (49)

Summary

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

Lightbulb On 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.