Added a new fast reading/writing engine to io.ascii

This PR adds a Cython/C parsing engine to the infrastructure of `io.ascii` so that new reading classes for simple formats (currently `FastBasic`, `FastTab`, `FastCsv`, `FastNoHeader`, `FastCommentedHeader`, and `FastRdb`) can opt to use this engine instead of the ordinary `BaseReader` inheritance model. The ordinary readers for these formats still remain to maintain flexibility and compatibility. The PR introduces a new parameter ``use_fast_reader`` in `ascii.read()` which can be used to enable or disable the fast engine (by default, `read()` will attempt to use the fast reader and fall back on the slow reader if parsing fails). The fast readers are also on the guess list directly in front of their slower counterparts.

There is also a Cython engine for writing with these formats; a similar parameter ``use_fast_writer`` can enable or disable this engine, and `ascii.write()` uses the engine by default when writing output in a compatible format.

Using randomly generated text files, it seems that the fast reading engine is anywhere from 3 to 7 times faster than the ordinary readers depending on the data type of table columns, while the fast writing engine is anywhere from ~2.5 to 12 times faster than the ordinary writers; both engines have less of a speed gain for floating-point data, which might be worth looking into at some point. [Here](http://amras1.github.io/astropy-benchmarks/#) are some before and after benchmarks, which cover a range of ASCII formats and compare Astropy's performance with that of numpy and Pandas. There is also a short design document [here](https://github.com/amras1/astropy-benchmarks/blob/master/design.md), which gives a quick overview of the parsing implementation in this PR.

Please feel free to make any suggestions or ask me anything.
I think there should be a Note here discussing guessing and the way it can slow down reading alot.
```
.. Note:: Guessing and Fast reading

   By default |read| will try to guess the format of in the input data by successively
   trying different formats until one succeeds ([reference the guessing section]).
   For the default `'ascii'` format this means that a number of pure Python readers
   with no fast implementation will be tried before getting to the fast readers.

   **For optimum performance**, turn off guessing entirely (`guess=False`) or narrow down the format
   options as much as possible by specifying the format (e.g. `format='csv'`) and/or other
   options such as the delimiter.
```