Thicket postprocessing

[pearce8]

Description

We will use Thicket for postprocessing performance results.

• Caliper modifiers. Caliper modifier "mode" determines what data is available in the .cali files after the run.
• Python (not ipython) script for "Canned" stacked plots in Thicket for "Plain" Caliper modifier
• Propagate experiment info to Caliper (Dewi); strong/weak use MPI ranks on x-axis, throughput uses problem size
• Add Caliper modifier for "Plain" + MPI; stacked plots should work for this as well
• Add mechanism to archive .cali files (how long), trigger Thicket python script with ramble analyze
• (later) post data on a dashboard

Dependencies: FIXME:Add a list of any dependencies.

Fixes issue(s): FIXME:Add list of relevant issues.

Type of Change

• { } Adding a system, benchmark, or experiment
• { } Modifying an existing system, benchmark, or experiment
• { } Documentation update
• { } Build/CI update
• { } Benchpark core functionality

Checklist:

If adding/modifying a system:

• { } Create a new directory for the system and a new system.py file
• { } Add a new dry run unit test in .github/workflows
• { } System appears in System Specifications table in docs catalogue section

If adding/modifying a benchpark:

• { } Add a new application.py and (maybe) package.py under a new directory
  for this benchmark
• { } Configure an experiment
• { } Benchmark appears in Benchmarks and Experiments table in docs catalogue
  section

If adding/modifying a experiment:

• { } Extend experiment.py under existing directory for specific benchmark
• { } Define a single node and multi-node experiments

If adding/modifying core functionality:

• { } Update docs
• { } Update .github/workflows and .gitlab/ci unit tests (if needed)