Add prefix ThreadsX. to functions from Base to get some speedup, if supported. Example:

using ThreadsX
ThreadsX.sum(sin, 1:10_000)

To find out functions supported by ThreadsX.jl, just type ThreadsX. + TAB in the REPL:

julia> using ThreadsX

julia> ThreadsX.
all       count     findall   findlast  mapreduce minimum   reduce    sort!
any       extrema   findfirst map       maximum   prod      sort      sum

ThreadsX.jl is aiming at providing API compatible with Base functions to easily parallelize Julia programs.

All functions that exist directly under ThreadsX namespace are public API and they implement a subset of API provided by Base. Everything inside ThreadsX.Implementations is implementation detail. The public API functions of ThreadsX expect that the data structure and function(s) passed as argument are thread-safe. For example, ThreadsX.sum(f, array) assumes that executing f(::eltype(array)) and accessing elements as in array[i] from multiple threads is safe.

In addition to the Base API, all functions accept keyword argument basesize::Integer to configure the number of elements processed by each thread. A large value is useful for minimizing the overhead of using multiple threads. A small value is useful for load balancing when the time to process single item varies a lot from item to item. The default value of basesize for each function is currently an implementation detail.

• Keyword argument dims is not supported yet.
• Keyword argument alg for sort functions is not supported.
• (There are probably more.)

Most of reduce-based functions are implemented as a thin wrapper of Transducers.jl.