My main use cases involve operations that I want to parallelize over the
last dimension of an array. In C/C++ I'd use #pragma parallel for or a
thread pool.
E.g., say I have a function f that operates in-place, like
function f(x,y)
for i=1:length(x)
y[i] = exp(x[i])
end
end
It would be nice to be able to use something like the current sync/async
syntax, but have it dispatch the function calls using threads instead of
processes.
X = zeros(1000000, 4)
Y = zeros(1000000, 4)
pool = ThreadPool(4)
@thread_sync pool begin
for p=1:size(X,2)
@thread_async pool begin
f(slice(X,:,p),slice(Y,:,p))
end
end
end
On Friday, March 13, 2015 at 3:52:37 AM UTC, Viral Shah wrote:
>
> I am looking to put together a set of use cases for our multi-threading
> capabilities - mainly to push forward as well as a showcase. I am thinking
> of starting with stuff in the microbenchmarks and the shootout
> implementations that are already in test/perf.
>
> I am looking for other ideas that would be of interest. If there is real
> interest, we can collect all of these in a repo in JuliaParallel.
>
> -viral
>
>
>
>
