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Diagnosing slow execution in BehaviorSpace

by Steve Railsback | Sep 2, 2022 | JASSS article updates

We recently discovered a memory issue that can cause BehaviorSpace to execute runs very slowly and using more processors than there are runs. A BehaviorSpace experiment using larger-than-usual model runs executed very slow, with the number of processors in use varying...

New time extension code examples

by Steve Railsback | Feb 3, 2022 | JASSS article updates, News

Four simple NetLogo models that demonstrate how to use the time extension are now available. These models contain code that can be copied and reused to: Create and use “Logotime” variables that contain dates (year, month, day), days (month and day), or...

Time extension now bundled with NetLogo 6.2!

by Steve Railsback | Jan 8, 2021 | JASSS article updates, OldNewsItems

The time extension to NetLogo makes it easy to use real dates and times, and time-series inputs and outputs, in NetLogo models. It also supports use of discrete-event simulation (models in which agents schedule future actions at specific times), as discussed in our...

New generation of processors allow large BehaviorSpace experiments on desktops

by Steve Railsback | Jun 4, 2020 | JASSS article updates

There are several lines of CPUs now available that can execute many BehaviorSpace runs simultaneously. Our experience is with AMD’s Ryzen processors, which provide from 12 up to 64 cores (24-168 threads that each can run one simulation). A Ryzen 9 processor with...

BehaviorSearch now packaged with NetLogo

by Steve Railsback | Aug 15, 2017 | JASSS article updates

Section 11 of our paper mentions the BehaviorSearch tool for fitting model parameters. BehaviorSearch is now packaged with NetLogo (version 6.0.1): Look for Behaviorsearch.exe in the same directory as NetLogo.exe.

More information on speeding up in-radius and in-cone statements

by Steve Railsback | Aug 15, 2017 | JASSS article updates

Robert Grider of the NetLogo development team clarified to us that NetLogo versions through 6.0 were optimized to use in-radius (and in-cone) on the built-in agentsets: turtles, patches, and any breeds that are defined. As a consequence, these primitives are slower...
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