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Re:DCompute: GPGPU with Native D for OpenCL and CUDA by VHRanger on Monday July 17, 2017 @03:47PM (#14791762)
> Another aspect of D that enables parallization is the use of ranges + algorithms.

Is that similar to the C++ std::algorithm execution policy features introduced in C++17?

Re:DCompute: GPGPU with Native D for OpenCL and CUDA by nicwilson on Monday July 17, 2017 @08:07PM (#14793356)
No. What Walter is talking about in D is if you have

Foo[] foo = ...;

foreach(f; foo) { f.bar.baz.quux; }

and the computation is parallelisable then you can write

import std.parallelism; foreach(f; parallel(foo)) { f.bar.baz.quux; }

and it will parallelised across threads.

I guess std.parallelism's parallel might be more analogous to an "instance" of an executor.

Re:DCompute: GPGPU with Native D for OpenCL and CUDA by VHRanger on Thursday July 20, 2017 @03:05PM (#14815386)
So that's similar to OpenMP parallel for looping?
Re:DCompute: GPGPU with Native D for OpenCL and CUDA by WalterBright on Monday July 17, 2017 @04:07PM (#14791897)
I'm not familiar with that aspect of C++17.
Re:DCompute: GPGPU with Native D for OpenCL and CUDA by nicwilson on Monday July 17, 2017 @08:11PM (#14793371)
Its the tag based dispatching for the `par` in

std::sort(par,a.begin(),a.end());

to call a parallel implementation of sort on `a`.