Alex Rivera | Logout

Automatic parallelization

Asked 2010-07-24T20:01:52.633
12

What is your opinion regarding a project that will try to take a code and split it to threads automatically(maybe compile time, probably in runtime).

Take a look at the code below:

for(int i=0;i<100;i++)
   sum1 += rand(100)
for(int j=0;j<100;j++)
   sum2 += rand(100)/2

This kind of code can automatically get split to 2 different threads that run in parallel. Do you think it's even possible? I have a feeling that theoretically it's impossible (it reminds me the halting problem) but I can't justify this thought.

Do you think it's a useful project? is there anything like it?

java multithreading project parallel-processing virtual-machine
Edit
Report

1 Answer

5

It's certainly possible, but it is an incredibly hard task. This has been the central thrust of compiler research for several decades. The basic issue is that we cannot make a tool that can find the best partition into threads for java code (this is equivalent to the halting problem).

Instead we need to relax our goal from the best partition into some partition of the code. This is still very hard in general. So then we need to find ways to simplify the problem, one is to forget about general code and start looking at specific types of program. If you have simple control-flow (constant bounded for-loops, limited branching....) then you can make much more head-way.

Another simplification is reducing the number of parallel units that you are trying to keep busy. If you put both of these simplifications together then you get the state of the art in automatic vectorisation (a specific type of parallelisation that is used to generate MMX / SSE style code). Getting to that stage has taken decades but if you look at compilers like Intel's then performance is starting to get pretty good.

If you move from vector instructions inside a single thread to multiple threads within a process then you have a huge increase in latency moving data between the different points in the code. This means that your parallelisation has to be a lot better in order to win against the communication overhead. Currently this is a very hot topic in research, but there are no automatic user-targetted tools available. If you can write one that works it would be very interesting to many people.

For your specific example, if you assume that rand() is a parallel version so you can call it independently from different threads then it's quite easy to see that the code can be split into two. A compiler would convert just need dependency analysis to see that neither loop uses data from or affects the other. So the order between them in the user-level code is a false depend

answered 2010-07-24T21:44:22.163

Your Answer