Multicore

Aspects

• Applications to run faster if we have multicore CPUs

  • Alternatively, several CPUs in a distributed setting

• Is the code going to run faster just by having more cores?

  • No!

  • It might if it has lots of non-interferent processes and no sequential bottlenecks

• Erlang uses all the cores on the SMP machine by default

  • Symmetric MultiProcessing

    erl -smp +S N 
    

  • The number N indicates how many schedulers (govern Erlang virtual machines)

  • Useful to test how the program works on different amount of cores

• Programming Erlang - Chapter 20

Speeding up programs on a multicore CPU

General guidelines

• Use lots of processes

  • To keep cores busy!

• Avoid side effects

  • Their order might change in the parallel version

• Avoid sequential bottlenecks

  • If the algorithm is intrinsically sequential, there is no much to do

• Write “small messages, big computations” code.

  • If computations are very small, it might be bigger the cost of spawning and messaging among processes

Making code run in parallel

code

• Definition of map

map(_, []) -> [];
map(F, [H|T]) -> [F(H)|map(F, T)].

• Can the application for each element be done in parallel?

pmap(F, Xs) ->
   S = self(),
   Ref = make_ref(),
   Pids = map(fun(X) -> spawn( fun() -> 
                                  S ! {self(), Ref, F(X)} 
                               end )
              end, Xs),
   gather(Pids, Ref).

gather([Pid|T], Ref) -> 
   receive
       {Pid, Ref, Ret} -> [Ret|gather(T, Ref)]
   end ;
gather([], _) -> [].

• map(F,L) =:= pmap(F,L)

  • Order of elements?

  • Side-effects?

  • What if the list is very big and the computation F very small?

---