All the performance comes from parallel processing

I often use this slide to show why all software has to be aware of parallel processing now.

In short, if your software does not exploit parallel processing techniques, then your code is limited to less than 2% of the potential performance of the processor. And this is just for a single processor - it is even more critical if the code has to run on a cluster or a supercomputer.

This is why NAG provides help to users and developers: training in parallel programming techniques; software development services to parallelize and scale your applications; advice and consulting; and our libraries - parallelized and tuned for a range of processors and co-processors.


  1. Very good! It is important to the developer.


Post a Comment

NAG moderates all replies and reserves the right to not publish posts that are deemed inappropriate.

Popular posts from this blog

Implied Volatility using Python's Pandas Library

C++ wrappers for the NAG C Library

ParaView, VTK files and endianness