Links
*****
The following is a link collection that contains different links that were useful for this project.

* Timing tools: 

    http://en.wikipedia.org/wiki/Time\_(Unix)

* Profiling tools:

    http://software.intel.com/en-us/intel-parallel-studio-xe
    
    http://en.wikipedia.org/wiki/LTTng
    
    http://code.google.com/p/gperftools/ 
    
    https://wiki.engr.illinois.edu/download/attachments/114688007/amplifier\_xe\_linux.pdf

* Tutorials:

    http://www.ibm.com/developerworks/library/l-gnuprof.html

    http://en.wikipedia.org/wiki/Performance\_analysis 

    http://en.wikipedia.org/wiki/Profiling\_(computer\_programming) 

    http://nbviewer.ipython.org/urls/raw.github.com/jrjohansson/scientific-python-lectures/master/Lecture-6B-HPC.ipynb

    http://www.softeng.rl.ac.uk/media/uploads/publications/2010/07/ProfilingTutorial.pdf

* Articles:  

    http://www.gotw.ca/publications/concurrency-ddj.htm 

    http://www.extremetech.com/computing/116561-the-death-of-cpu-scaling-from-one-core-to-many-and-why-were-still-stuck/

    http://web.mit.edu/newsoffice/topic/the-multicore-future.html 

    http://www.karlrupp.net/2013/06/cpu-gpu-and-mic-hardware-characteristics-over-time/

* Fitting:  

    http://jarrodmillman.com/scipy2011/pdfs/brefsdal.pdf 

    http://adsabs.harvard.edu/abs/1979ApJ...228..939C

* General links:
  
    http://www.debugging-guide.com/ 

    http://spiff.rit.edu/classes/phys445/lectures/radec/radec.html

* Google Performance Tools:  

    http://code.google.com/p/gperftools/?redir=1

* Simple Python Profiling tutorial:
 
    http://nematodes.org/martin/teaching/programming-topics/profiling-python-for-cpu-and-memory-usage/

* Online courses 

    http://www-users.york.ac.uk/~mijp1/teaching/4th\_year\_HPC/notes.shtml

    http://www.citutor.org

* Books:  
    
    Quinn, "Parallel Programming in C with MPI and OpenMP", `Amazon <http://amzn.com/0072822562>`_  
    
    Grötker, "Developer's Guide to debugging", `Amazon <http://amzn.com/1470185520>`_