Is there a simple way to run a C/C++ program parallelly without recoding?

c, multicore, multithreading, parallel-processing

Solution

I have a multi-cores machine but when i tried to run this old C program (http://www.statmt.org/moses/giza/mkcls.html) it only utilizes one core. Is there a way to run the C code and send the cycles/threads to the other cores?

Without recompiling, definitely not.

You may be able to make some minor tweaks and use a tool that takes your source and parallelizes it automatically, but since each core is quite separate - they are "quite far apart" - you can't just spread the instructions between the two cores. The code has to be compiled in such a way that there are two "streams of instructions" - if you were to just send every other instruction to every other core in a dual core system, it would probably run 10-100 times slower than if you run all code on one core, because of all the extra overhead in communication between the cores that would be needed [each core already has the ability to run several instructions in parallel, and the main reason for multi-core processors in the first place is that this ability to run things in parallel only goes so far at making things faster - there are only so many instructions that can be run before you need the result of a previous instruction, etc, etc].

Is recoding the code into CUDA the only way?

No, there are many other alternatives. OpenMP, hand-coding using multiple threads. Or, the simplest approach, start the program two or four times over, with different input data, and let them run completely separately. This obviously only works if there is something you can run multiple variants of at the same time...

A word on "making things parallel". It's not a magical thing that will make all code faster. Calculating something where you need the result of the previous calculation would be pretty hopeless - say you want to calculate Fibonacci series for example - `f(n) = f(n-1) + f(n-2)` - you can't do that with parallel calculations, because you need the result from the other calculation(s) to proceed this. On the other hand, if you have a dozen really large numbers that you want to check if they are prime-numbers, then you'd be able to do that about four times faster with a 4 core processor and four threads.

If you have a large matrix that needs to be multiplied by another large matrix or vector, that would be ideal to split up so you do part of the calculation on each core.

I haven't looked at the code for your particular project, but just looking at the description, I think it may parallelise quite well.

Problem

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