Large data issues for parallel computations#

Among the challenges in visualizing the results of parallel computations is dealing with the large amount of data. The first bottleneck this presents is during run-time when ASPECT wants to write the visualization data of a time step to disk. Using the compressed VTU format, ASPECT generates on the order of 10 bytes of output for each degree of freedom in 2d and more in 3d; thus, output of a single time step can run into the range of gigabytes that somehow have to get from compute nodes to disk. This stresses both the cluster interconnect as well as the data storage array.

There are essentially two strategies supported by ASPECT for this scenario:

  • If your cluster has a fast interconnect, for example Infiniband, and if your cluster has a fast, distributed file system, then ASPECT can produce output files that are already located in the correct output directory (see the options in Global parameters) on the global file system. ASPECT uses MPI I/O calls to this end, ensuring that the local machines do not have to access these files using slow NFS-mounted global file systems.

  • If your cluster has a slow interconnect, e.g., if it is simply a collection of machines connected via Ethernet, then writing data to a central file server may block the rest of the program for a while. On the other hand, if your machines have fast local storage for temporary file systems, then ASPECT can write data first into such a file and then move it in the background to its final destination while already continuing computations. To select this mode, set the appropriate variables discussed in Subsection: Postprocess / Visualization. Note, however, that this scheme only makes sense if every machine on which MPI processes run has fast local disk space for temporary storage.


An alternative would be if every processor directly writes its own files into the global output directory (possibly in the background), without the intermediate step of the temporary file. In our experience, file servers are quickly overwhelmed when encountering a few hundred machines wanting to open, fill, flush and close their own file via NFS mounted file system calls, sometimes completely blocking the entire cluster environment for extended periods of time.