4
$\begingroup$

I'm nearly graduated in computer science engineering and my thesis should discuss the massively parallel computational model of CUDA and its advantages/applications.

I'm searching for an application field (an idea) to show off some of CUDA capabilities and (definitely) also my skills as programmer and engineer.

I'm up for a bit of challenge to integrate an interesting work into my thesis project and discussion so I'm asking for advices or ideas

Improve this question
$\endgroup$
6
  • 1
    $\begingroup$ Try cracking md5 :) $\endgroup$
    – Pratik Deoghare
    Feb 1, 2012 at 13:25
  • $\begingroup$ That's not a bad idea, I was searching for something more original but this isn't bad though $\endgroup$
    – Paul
    Feb 1, 2012 at 15:18
  • 1
    $\begingroup$ Ok, I feel stupid, but: what is CUDA? Should the readers of this website know the meaning of this word without explanation? $\endgroup$
    – Tsuyoshi Ito
    Feb 1, 2012 at 16:22
  • 1
    $\begingroup$ I think you will get better answers over at scicomp.SE. $\endgroup$
    – Raphael
    Feb 1, 2012 at 20:20
  • 2
    $\begingroup$ I think this might violate our policy on project topics, I have started a discussion on meta and voted to close for now. $\endgroup$
    – Artem Kaznatcheev ♦
    Feb 1, 2012 at 23:43

5 Answers 5

Reset to default
0
$\begingroup$

I would be interested in integration of GPU processsing (wether CUDA does not matter) into standard compilers. Can you figure out where application makes sense programmatically? Can you efficiently use GPUs?

Improve this answer
$\endgroup$
2
  • $\begingroup$ not bad this one too :D $\endgroup$
    – Paul
    Feb 1, 2012 at 20:57
  • $\begingroup$ If you like this not very theoretical answer, you might want to ask your question over at scicomp.SE. $\endgroup$
    – Raphael
    Feb 9, 2012 at 21:04
5
$\begingroup$

Build a "CUDA-SAT solver" and outperform the winners of the annual Sat competitions ! :-)

Edit: I posted the answer quickly ... but - after a Google search - I found that my idea is not so original, see: NVIDIA CUDA Architecture-based Parallel Incomplete SAT Solver ... however I think that a public available project/source code of a CUDA-powered SAT solver that can be compiled and used on a standard PC (Linux and/or Win) equipped with a CUDA GPU graphics card would be very appreciated.

As a second best, I suggest you to try to implement a parallel genetic algorithm and pick one (or more) of the many possible applications to show the performance gains due to the parallelization.

Improve this answer
$\endgroup$
3
  • $\begingroup$ this one's good too: GA with cuda, interesting.. although it has already been done $\endgroup$
    – Paul
    Feb 1, 2012 at 20:17
  • 1
    $\begingroup$ ... probably you already know it, but if you're looking for some original CUDA applications, you must take a look to this page, too: nvidia.it/object/cuda_apps_flash_it.html ... the task seems not so easy :-( ... $\endgroup$
    – Marzio De Biasi
    Feb 1, 2012 at 22:51
  • $\begingroup$ You're totally right, seems hard $\endgroup$
    – Paul
    Feb 10, 2012 at 13:24
3
$\begingroup$

the protein folding problem seems a good candidate; its a hot area of bio-informatics & already highly parallelized via some apps, (folding@home) and there is a large community holding bi-yearly contests & prizes for solutions see eg CASP. good/effective/accurate solutions are quite scientifically and commerically valuable and some are patented. the difficulty in this area (in contrast to eg the other good candidate given by Vor, SAT) is that some of the algorithms could probably be very difficult to implement solely from papers.

Improve this answer
$\endgroup$
0
$\begingroup$

It depends on how much time and effort you want to spend for it. I think, cracking md5 is not a very time consuming job since you need to implement a simple brute-force search algorithm only.

Integrating the power of GPUs into an existing programming language would be a great idea since many other applications such as the ones mentioned by other answers can be written using such a language. I'd prefer to do the job in such a way which is either transparent to the user or he needs only a little effort to use the capability.

One idea is to write an object file optimizer or alter an open source compiler which looks for specific patterns (like loops with simple body) in programs and replaces them with a CUDA version. That might be too much job to do.

The other option is to implement a simple matrix library with matlab-like operations. In C++, it would look like this:

CUDAArray<int> a = CUDAArray<int>(1000);
CUDAArray<int> b = CUDAArray<int>(1000);
// Use GPU to compute
CUDAArray<int> c = a * 2 + b;

Anyways, I think non of these ideas is a new one.

Improve this answer
$\endgroup$
0
$\begingroup$

I may be wrong, but I think that a GPU implementation of parallel graph partitioning is missing. This would be of great value, and you could compare the performances obtained with ParMetis and Zoltan, which are standard parallel implementations of graph partitioning. Why graph partitioning ? Because it is suitable for irregular, unstructured communication patterns lacking a well-known graph topology, a feature of many graph-based applications. Your work will be useful to many people working in the field.

You may choose to implement just a single technique (e.g., Space-Filling Curves), or a little library. Finally, did you consider implementing your work using OpenCL ? While CUDA is a proprietary technology, OpenCL is a standard and you code will run on any current GPU device.

Improve this answer
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.