Quantum computers and algorithm performance [closed] - algorithm

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Closed 10 years ago.
I have a question. Gradually quantum computers will emerge someday. So, nowadays making algorithm efficient is important; I mean, making it optimal to run as fast as possible. But once quantum PC emerges does the algorithm performance improvements are still important?
Cheers

Quantum algorithms have the possibility of searching a complete number space for an answer in one go, that much is true. However, the algorithm you choose will still determine how many of these steps are needed, and whether you can pack the whole space with useful inputs.

I think its too early to worry about it. It also might be quantum computer will never made.

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What are some good algorithms to generate a dynamic heightmap? [closed]

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Closed 9 years ago.
I want to research some algorithms for dynamic heightmap generation but I'm not familiar with any. Getting even more dynamic. Whats some theory on how multi-dimensional heightmaps work? i.e. Caves and overhangs. Should I use multiple heightmap images or complex algorithms?
For simple 2D heightmaps the Diamond-square algorithm produces reasonable results, and is fast. There are a few things you can apply over the top of that to make it look more realistic, such as simple erosion, while still being very fast.
For more interesting features... if you want fast results, I'd stick with a 2D heightmap and then add secondary feature entities (i.e. boulders and holes), rather than try to generate a true 3D environment; but of course whether that comes close to being enough depends entirely on what you want to achieve.

VHDL for scientific computing [closed]

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Closed 10 years ago.
I was wondering if folks use VHDL/FPGAs in scientific computing.
An example scenario that I was thinking off was say:
Construct an arbitrary precision floating point adder
Configure an FPGA board to then add such numbers
So I was looking for references (example code) where VHDL/FPGAs have been used in scientific computing.
Thanks in advance.
There are several vendors who build heterogeneous computing systems using FPGAs. I doubt you'll find complete source code for such systems.
SRC Computing
Convey Computer
Mitrionics. A reseller of other systems.
Novo-G. An academic project.
Look into radio astronomy. With arrays such as the VLA and ALMA, the massively parallel correlator is the part that could be considered most important. These typically use FPGAs but could use custom-designed chips for extreme performance at higher cost.
Some fine reading:
https://science.nrao.edu/facilities/cdl/digital-signal-processing
http://web.njit.edu/~gary/728/Lecture8.html

Cortical learning implementation (Numenta's HTM theory) [closed]

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Closed 11 years ago.
Has anyone tried to implement Numenta's most recent cortical learning theory (http://www.numenta.com)? I'm working on it and would like to share experience.
I think the ideas from Numeta are very promising. But as with any company that wants to make money they are not verbose enough about the technology so that one should be able to re-implement their system (at least from what I have seen so far). It is probably not in their interest that one could just rebuild the system from which they plan to make money.
Also their system is very general and complex. So unless you have a lot of experience with other kinds of neural networks and learning algorithms, I would not recommend experimenting with their ideas. First try to do Backpropagation and maybe some of the less advanced temporal learning until you are really familiar with that.

Does anyone know the algorithm used for navigating a Pac-Man maze? [closed]

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Closed 10 years ago.
I need an algorithm for this pacman maze. Can anyone help?
You don't say what kind of algorithm you want, but if you are implementing the movement of the ghosts, then you should read "Understanding Pac-Man Ghost Behavior" by Chad Birch.
That's quite a large question.
Anyway, I've yet written a Pac-Man game in both Java and C and I implemented the maze as a matrix filled as follows:
- "-1" if there's a wall;
- "1" if there's a candy;
- else, "0".
To navigate through the maze, you have to use key events. When you'd like to turn left or right, you test if there's a wall ("-1").
I don't know if this answered your question, but feel free to precise if it's not the case.
Another site with quite some informations on pacman is the PacMan dossier

Algorithm to understand meaning [closed]

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Closed 11 years ago.
I want to know if is there any specific algorithm that can be followed to understand the meaning of a word/sentence/paragraph. Basically, I want to write a program that will take text/paragraph as input and try to find out what its meaning is. And thereby highlight the emotions within the text.
Also, if there is an algorithm to understand things, can the same algorithm be applied to itself? It reduces the quest further to a point where we become interested in knowing meaning of meaning OR rather definition of definition.
You want Natural Language Processing and Semantic Technology. This is still a flourishing area in computer science. Look at things such as a Semantic Reasoner. You can start with Jena. There are also other things you can look at such as Academic Thesis papers.

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