godmodder

Hello,

 

My application is 32-bit and runs fine on huge datasets in 64-bit Ubuntu. Memory usage goes up to about 6.7GB of RAM.

However, on 64-bit Windows I get std::bad_alloc exceptions, presumably because I'm limited to 2GB of virtual address space for 32-bit apps. I have tried to link with the /LARGEADDRESSAWARE flag, which increases this limit. Indeed this seems to stall the crash, but around 4GB it still fails.

 

Is there a way to circumvent this limitation in Windows, without resorting to full porting to 64-bit? Why doesn't Ubuntu suffer from this limitation, as after all the application is 32-bit on there as well?

 

Thanks,

Jeroen

Hello, everyone!

I had a session today with my colleagues to practise the defense for an important scholarship. One of the work packages in my project is the determination of the lower bound complexity of a specific new algorithm. The colleagues questioned whether I would be able to define bounds on the complexity of the problem before finding an algorithm that actually solves the problem.

Now I'm sure this must be possible because, if one takes sorting as an example for instance, it doesn't take long to realise that one needs to iterate over at least every element to sort a whole array (hence linear complexity as the absolute lower bound). In practise ofcourse average sorting complexity will be n log n. It seems like a conclusion one could arrive at before knowing even one sorting algorithm.

Is it possible to determine complexity bounds of a problem before discovering an actual algorithm? If so, did this happen before (like with sorting e.g.), so I could use that particular case to motivate my answer?

Thanks very much,
Jeroen

Hi,

I'm researching inverse rendering: extraction of the lighting, materials and geometry out of photos from different viewpoints.
The current algorithm uses a hierarchical refinement procedure, based on a Haar wavelet tree, to guide the optimization process. The process is illustrated below:



As you can see, the estimated lighting is not smooth enough. In game development the most obvious thing to do would be to apply some smoothing filter, but I cannot do it in this case. This would make my estimation much more innaccurate and this is not meant for games but more critical visualisation applications.

So my idea was to replace the Haar wavelets with linear wavelets. Unfortunately, there is far less literature on them.
As we all know, Haar wavelets look like this:



However, I've been scratching my head over what a linear (second order) wavelet would look like. Would it look something like this?


Also, if you know of any good literature on linear wavelets like these, please let me know.

Many thanks,
Jeroen