Open isaacsas opened 1 month ago
Relevant benchmarks to look at:
Catalyst paper: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011530
SciMLBenchmarks: https://docs.sciml.ai/SciMLBenchmarksOutput/stable/
And probably we should cook up some hybrid models and variable rate jump models to test with too.
There are several variables that affect the relative performance of SSAs in the order of importance:
Direct
and better performance of e.g. RSSA-CR
(and other more advanced SSAs).RSSA
and RSSA-CR
.RDirect
, Direct-CR
, RSSA-CR
.@isaacsas , am I forgetting anything in this list?
Ideally, we would cook up an example of a network that varies one of these dimensions and holds others constant for a fair comparison. One convenient way of cooking up examples is to make a spatial massaction jumps network and use a non-spatial SSA, so that the number of spatial species is proportional to the number of nodes in the spatial graph.
That sounds like a good list for what can be examined (more) easily.
https://github.com/SciML/JumpProcesses.jl/pull/351 adds a default algorithm, but we should follow up and benchmark / examine existing benchmarks to better determine where the switch points between methods should be.