Julia artifacts are pieces of data that can be distributed alongside a package. Julia artifacts were developed to distribute application binaries (e.g., compiled libraries). In CliMA, we use them to distribute data required to perform our simulations (e.g., input data).

The ClimaArtifacts module extends the Julia artifact system to solve two issues:

  1. Ensuring that artifacts can be gracefully acquired by parallel runs;
  2. Tagging artifacts that are accessed during a simulation.

We will examine these two problems below. In the meantime, this entire documentation page can be summarized in a one short directive for package developers:

Instead of accessing artifacts with ArtifactWrappers.jl or using Julia artifacts directly, use the @clima_artifact macro instead.

Also, keep in mind that

⚠️ Note: Julia artifacts are always entire folders, never single files!

Julia artifacts and MPI

Package developers can specify one of two modes for any given artifact: greedy (default) or lazy download. Artifact that are not marked as lazy are automatically downloaded by Julia when the package is instantiated. On the other hand, lazy artifacts are downloaded the first time they are accessed.

CliMA packages can distribute tens of artifacts that are relevant for very different types of simulations, and it is a good idea to mark artifacts as lazy unless they are strictly required for the operation of the package (e.g., the orbital parameters in Insolation.jl).

Lazy artifacts are incompatible with MPI. In parallel runs, each process tries to download the same file, resulting in a race condition and corrupted files (not to mention tens of processing pinging the same server at the same time). ClimaArtifacts implements a new macro, @clima_artifact, to solve this problem.

@clima_artifact is a near drop-in replacement for the @artifact_str Julia macro.

For greedy artifacts and non-MPI runs, it is possible to simply call @clima_artifact(artifact_name). This will return the path of the artifact folder. This macro will fail for lazy artifacts. In that case, one has to also pass the ClimaComms.jl context. The context is required because @clima_artifact needs to synchronize different MPI processes.


This extension is loaded when loading ClimaComms

Assume socrates is a lazy artifact, we can access the socrates artifact folder as in

using ClimaUtilities.ClimaArtifacts
# If the artifact is lazy, we also need LazyArtifacts
using LazyArtifacts

import ClimaComms
# When loading ClimaComms, a Julia extension for ClimaUtilities will be loaded

my_mpi_context = ClimaComms.context()

socrates_path_folder = @clima_artifact("socrates", context)

The @clima_artifact macro is executed at parse time when the argument is a literal string (e.g., @clima_artifact("socrates")), and at runtime when it is a variable @clima_artifact(artifact_name).

Tagging artifacts

A full climate simulation requires lots of external input data. Most of this data comes from scientific experiments that have to be properly acknowledged. ClimaArtifacts allows users to know what artifacts were used in a given simulation. As long as artifacts are being accessed with @clima_artifacts, the ClimaArtifacts keeps track of what is being used. The set of artifacts accessed can be obtained with ClimaArtifacts.accessed_artifacts.


using ClimaUtilities.ClimaArtifacts
art1 = @clima_artifact("socrates")
art2 = @clima_artifact("zeno")

# Set(["socrates", "zeno"])


@clima_artifact(artifact_name, context = nothing)

Return the path of the given artifact name. The path is always a folder (Julia artifacts can contain multiple files).

This macro plays nicely with MPI contexts and lazily downloaded artifacts. This is achieved by ensuring that only one process downloads the file, while the other wait until the file is fully downloaded.

Passing the context is required only for lazy artifacts.