Utilities

Single-threaded Speed-up

The Julia scheduler is running on thread 1. If your application uses tasks or channels on thread 1 (e.g. with process!), it has to compete against other background tasks. You can remove this competition and speed up your application significantly (often by $\times10$ or more) by moving it to a thread other than 1.

DiscreteEvents.onthread — Function

onthread(f::F, tid::Int; wait::Bool=true) where {F<:Function}

Execute a function f on thread tid.

To execute f on a thread other than 1 can speed it up significantly if it depends on asynchronous tasks.

Arguments

f::Function: function to execute
tid::Int: thread id
wait::Bool=true: if true, it waits for function to finish

Example

julia> using DiscreteEvents, .Threads

julia> onthread(2) do; threadid(); end
2

source

Look at the M/M/c benchmarks and to this example on DiscreteEventsCompanion for an illustration. You cannot speedup applications not using tasks or channels with this technique.

Parallel RNG Seed

DiscreteEvents.pseed! — Function

pseed!(s::Int)

Seed each of the thread local RNGs with s*threadid() to get reproducible, but different random number sequences on each thread.

source