Parallization options

WSClean can exploit parallelism by using multiple threads and by using multiple MPI processes. The MPI processes may run at different compute nodes, which enables distributed processing.

Multi-threading

WSClean has several command-line options for configuring multi-threading:

• Number of cores to use: -j <N>

  Tells WSClean to use N threads. By default, WSClean uses as many threads as there are cores in the system. WSClean uses this setting everywhere possible, including when WSClean uses external libraries, such as IDG and Radler.

• Do parallel deconvolution: -parallel-deconvolution <maxsize>

  Tells WSClean to do parallel deconvolution where maxsize is the maximum subimage size. For more information, see parallel deconvolution.

• Reduce memory usage for deconvolution: -deconvolution-threads <N>

  On machines with a large number of cores, using less deconvolution threads helps if WSClean runs out of memory during deconvolution. WSClean allocates memory for each thread, e.g., for storing the sub-image a number of times.

  This option tells WSClean to use a maximum of N threads during deconvolution. The default value is the number of threads as specified using the -j argument.

• Enable parallel reordering: -parallel-reordering <N>

  Tells WSClean to use parallelism when reordering the input measurement sets on disk. WSClean uses one reordering task for each input measurements set, and executes up to N tasks in parallel.

  Reordering is bound by disk speed when the number of cores is high. Using 4 reordering threads is generally a good balance between disk and CPU speed. By default, WSClean therefore uses 4 reordering threads, even if -j is specified. The optimal number of reordering threads depends on disk speed.

• Enable parallel gridding: -parallel-gridding <N>

  Tells WSClean to use N threads during gridding and degridding. By default, parallel gridding is disabled, even if -j is specified. Parallel gridding does not work with the idg gridder, or when using MPI (see below).

  The gridders themselves also exploit parallelism internally, however, gridders can’t always scale well to all cores, in particular when using beam or h5parm corrections. In these cases, using parallel gridding might yield better performance.

  All gridders get an amount of threads equal to the total number of threads, divided by the number of parallel gridders, rounded up. For example, -parallel-gridding 3 -j 16 yields 3 parallel gridders that use 6 threads each.

Distributed imaging

WSClean allows the use of multiple nodes for imaging. This is described in the distributed imaging section.