[Cython] cython.parallel tasks, single, master, critical, barriers

[Dag Sverre Seljebotn]

On 10/09/2011 02:18 PM, Dag Sverre Seljebotn wrote:
> On 10/09/2011 02:11 PM, mark florisson wrote:
>> Hey,
>>
>> So far people have been enthusiastic about the cython.parallel features,
>> I think we should introduce some new features. I propose the following,
>
> Great!!
>
> I only have time for a very short feedback now, perhaps more will follow.
>
>> assume parallel has been imported from cython:
>>
>> with parallel.master():
>> this is executed in the master thread in a parallel (non-prange)
>> section
>>
>> with parallel.single():
>> same as master, except any thread may do the execution
>>
>> An optional keyword argument 'nowait' specifies whether there will be a
>> barrier at the end. The default is to wait.

I like

if parallel.is_master():
     ...
explicit_barrier_somehow() # see below

better as a Pythonization. One could easily support is_master to be used 
in other contexts as well, simply by assigning a status flag in the 
master block.

Using an if-test flows much better with Python I feel, but that 
naturally lead to making the barrier explicit. But I like the barrier 
always being explicit, rather than having it as a predicate on all the 
different constructs like in OpenMP....

I'm less sure about single, since making it a function indicates one 
could use it in other contexts and the whole thing becomes too magic 
(since it's tied to the position of invocation). I'm tempted to suggest

for _ in prange(1):
     ...

as our syntax for single.

>>
>> with parallel.task():
>> create a task to be executed by some thread in the team
>> once a thread takes up the task it shall only be executed by that
>> thread and no other thread (so the task will be tied to the thread)
>>
>> C variables will be firstprivate
>> Python objects will be shared
>>
>> parallel.taskwait() # wait on any direct descendent tasks to finish
>
> Regarding tasks, I think this is mapping OpenMP too close to Python.
> Closures are excellent for the notion of a task, so I think something
> based on the futures API would work better. I realize that makes the
> mapping to OpenMP and implementation a bit more difficult, but I think
> it is worth it in the long run.
>
>>
>> with parallel.critical():
>> this section of code is mutually exclusive with other critical sections
>> optional keyword argument 'name' specifies a name for the critical
>> section,
>> which means all sections with that name will exclude each other,
>> but not
>> critical sections with different names
>>
>> Note: all threads that encounter the section will execute it, just
>> not at the same time

Yes, this works well as a with-statement...

..except that it is slightly magic in that it binds to call position 
(unlike anything in Python). I.e. this would be more "correct", or at 
least Pythonic:

with parallel.critical(__file__, __line__):
     ...


>>
>> with parallel.barrier():
>> all threads wait until everyone has reached the barrier
>> either no one or everyone should encounter the barrier
>> shared variables are flushed

I have problems with requiring a noop with block...

I'd much rather write

parallel.barrier()

However, that ties a function call to the place of invocation, and 
suggests that one could do

if rand() > .5:
     barrier()
else:
     i += 3
     barrier()

and have the same barrier in each case. Again,

barrier(__file__, __line__)

gets us purity at the cost of practicality. Another way is the pthreads 
approach (although one may have to use pthread rather then OpenMP to get 
it, unless there are named barriers?):

barrier_a = parallel.barrier()
barrier_b = parallel.barrier()
with parallel:
     barrier_a.wait()
     if rand() > .5:
         barrier_b.wait()
     else:
         i += 3
         barrier_b.wait()


I'm really not sure here.

>>
>> Unfortunately, gcc again manages to horribly break master and single
>> constructs in loops (versions 4.2 throughout 4.6), so I suppose I'll
>> first file a bug report. Other (better) compilers like Portland (and I'm
>> sure Intel) work fine. I suppose a warning in the documentation will
>> suffice there.
>>
>> If we at some point implement vector/SIMD operations we could also try
>> out the Fortran openmp workshare construct.
>
> I'm starting to learn myself OpenCL as part of a course. It's very neat
> for some kinds of parallelism. What I'm saying is that at least of the
> case of SIMD, we should not lock ourselves to Fortran+OpenMP thinking
> too early, but also look forward to coming architectures (e.g., AMD's
> GPU-and-CPU on same die design).
>
> Dag Sverre
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