Analysis Tools

Task dependencies

At the beginning of each simulation the file dependency_graph.csv is generated and can be transformed into a dot and a png file with the script tools/ It requires the dot package that is available in the library graphviz. This script has also the possibility to generate a list of function calls for each task with the option --with-calls (this list may be incomplete). You can convert the dot file into a png with the following command dot -Tpng -o dependency_graph.png or directly read it with the python module xdot with python -m xdot

Cell graph

An interactive graph of the cells is available with the configuration option --enable-cell-graph. During a run, SWIFT will generate a cell_hierarchy_*.csv file per MPI rank. The command tools/ cell_hierarchy_*.csv merges the files together and generates the file cell_hierarchy.html that contains the graph and can be read with your favorite web browser.

With chrome, you cannot access the files directly, you will need to either access them through an existing server (e.g. public http provided by your university) or install npm and then run the following commands

npm install http-server -g
http-server .

Now you can open the web page http://localhost:8080/cell_hierarchy.html.

Memory usage reports

When SWIFT is configured using the --enable-memuse-reports flag it will log any calls to allocate or free memory that make use of the swift_memalign(), swift_malloc(), swift_calloc() and swift_free() functions and will generate a report at the end of each step. It will also attempt to dump the current memory use when SWIFT is aborted by calling the error() function. Failed memory allocations will be reported in these logs.

These functions should be used by developers when allocating significant amounts of memory – so don’t use these for high frequency small allocations. Each call to the swift_ functions differs to the standard calls by the inclusion of a “label”, this should match between allocations and frees and ideally should be a short label that describes the use of the memory, i.e. “parts”, “gparts”, “hydro.sort” etc.

Calls to external libraries that make allocations you’d also like to log can be made by calling the memuse_log_allocation() function directly.

The output files are called memuse_report-step<n>.dat or memuse_report-rank<m>-step<n>.dat if running using MPI. These have a line for each allocation or free that records the time, step, whether an allocation or free, the label, the amount of memory allocated or freed and the total of all (labelled) memory in use at that time.

Comments at the end of this file also record the actual memory use of the process (including threads), as reported by the operating system at the end of the step, and the total memory still in use per label. Note this includes memory still active from previous steps and the total memory is also continued from the previous dump.