I will be giving an introductory how-to talk on constrained DFT at the 2018 CP2K UK User meeting at the University of Lincoln, UK, on Friday January 12 2018.
In my previous post, I discussed the benefits of using the message passing interface (MPI) to parse large data files in parallel over multiple processors. In today’s post, I will demonstrate how MPI I/O operations can be further accelerated by introducing the concept of hints. The second topic I will discuss is the emergence of solid-state drives in high-performance computing systems to resolve I/O bottlenecks. These topics will be illustrated by benchmark calculations using a parallel writer routine that I will implement to the task described previously.
Lately, parsing volumetric data from large (> 300 MB) text files has been a computational bottleneck in my simulations. Because I expect to be processing hundreds of these files, I decided to parallelize the parser routine by leveraging the message passing interface (MPI). I will describe my first experience with MPI I/O in this post by going through the synthesis process of the parallelized parser routine. I will also examine the performance of the parallel parser.
Compiling a CP2K binary – the massively parallel, open-source quantum chemistry and solid state physics program written in Fortran 2003 – can be a daunting task if you’ve never built a large project using maketools. This post aims to demystify the build process by showcasing a full CP2K build on a Cray XC40 supercomputer (codename Sisu) including dependencies.
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