dsimcha wrote:
== Quote from Charles Hixson ([email protected])'s article
dsimcha wrote:
I've created an alpha release of parallelFuture, a high-level parallelization
library for D2. Right now, it has a task pool, futures, parallel foreach, and
parallel map.
Here's the (IMHO) coolest example:
auto pool = new ThreadPool();
// Assuming we have a function isPrime(), print all
// prime numbers from 0 to uint.max, testing for primeness
// in parallel.
auto myRange = iota(0, uint.max);
foreach(num; pool.parallel(myRange)) {
if(isPrime(num)) {
synchronized writeln(num);
}
}
The interface is there and it seems to work, although it has not been
extensively stress tested yet. Some of the implementation details could
admittedly use some cleaning up, and I would appreciate help from some
threading gurus on improving my queue (right now it's a naive synchronized
singly-linked list) and getting condition mutexes to work properly. (Right
now, I'm using atomic polling followed by sleeping for 1 millisecond in a lot
of places. It's a kludge, but it seems to work reasonably well in practice.)
The code is at:
http://dsource.org/projects/scrapple/browser/trunk/parallelFuture/parallelFuture.d
The docs are at:
http://cis.jhu.edu/~dsimcha/parallelFuture.html
If you can easily do it, it would be nice to be able to have the threads
able to communicate with each other. Something along the lines of both
broadcast messages and 1:1 exchanges. A very rough sketch of a possible
use:
Task[] tasks = Task.who_is_waiting;
foreach (auto task; tasks)
{ if (task.process(something) )
{ task.markDone(true); }
}
I see "something" as being an Object that would need to implement an
interface to carry some identifying information, so when a task received
it it could determine what to do with it (with "reject processing" being
an option). I think the rest is pretty clear.
OTOH, this comment was just to demonstrate the kind of communication
between tasks that I'm talking about. Static methods for broadcast
communication and instance methods for 1:1 communication. With
safeties, so when a task completes before it gets your message, you
aren't left talking to a null pointer. Cleanup would need to be managed
by the original thread that created the tasks. It would need to be able
to send a broadcast "now closing task xxx signal" to all threads.
Threads maintaining a list of tasks would need to scan through them and
remove any references to that task.
Maybe this is getting to complicated, but it would certainly be useful.
In the past interthread communication is the main problem that's kept
me from using them.
I'll think about this and see if I can work something like this in, but I need
real-world use cases. I do bioinformatics work, which basically means
large-scale
data mining, embarrassingly parallel problems and very CPU-bound work. The use
cases I had in mind were mostly the "use every core I have to do something
embarrassingly parallel" kind. The goal was to make these use cases as dead
simple as possible.
Whatever use cases you have in mind, I'm apparently not familiar with them. If
I'm to improve this lib to handle use cases other than the pure
throughput-oriented parallelization of embarrassingly parallel tasks that I had
in
mind, I need to understand use cases from other fields.
It's basically a simplified form of message passing, and useful for
general processing in the context of multiple cores. If you wanted to
implement, say, Smalltalk or Objective-C you could use this to allow
their calls to proceed in parallel. My particular interest is based on
AI. I'm not talking about neural-nets, as that, I think, would incur
too much overhead if implemented with even this kind of simplified
message passing, but one where several "dumb" processes are continually
running in the background and sending messages whenever they detect
something interesting. (So it would also be useful if the tasks could
be assigned an adjustable priority.)
The kind of system I'm envisioning should be able to adjust to a
variable number of processors...even variable while the program is
running. (Yeah, that's not what we're talking about here. I'm talking
about the higher level design.)
Erlang can probably do what I want, but it's incredibly slow. In tests
I've run it's come out even slower than Ruby, which is slower than
Python. Currently my choice is between D and Java. with a preference
for D. Java has the libraries, but D is a better design fit with what I
want to do.
(I can't give detailed specifics, because I haven't yet done any
programming of that part of the process. But the rough design calls for
lots of small modules with a coordinator that manages them. I don't
like having the coordinator be so central, but every threading model
I've seen has a central controller. I'd really rather do something more
like Linux/Unix daemons (see the Pandemonium paper, which may have
originally inspired Unix).
