Working on compiler IR is a daunting task. I have therefore added a new system property `enso.compiler.dumpIr` that will help with that. It dumps the encountered IRs to `ir-dumps` directory in the [GraphViz](www.graphviz.org) format. More info in updated docs.
Note that all the functionality to dump IRs to `dot` files was already implemented. This PR just adds the command line option and updates docs.
# Important Notes
- `--dump-graphs` cmd line option is removed as per [Jaroslav's request](https://github.com/enso-org/enso/pull/10740#pullrequestreview-2216676140).
- To dump graphs, use `-Dgraal.Dump=Truffle:2` system property passed via `JAVA_OPTS` env var.
If you run `env JAVA_OPTS='-Denso.compiler.dumpIr=true' enso --run tmp.enso` where `tmp.enso` is, e.g.:
```
from Standard.Base import all
main = 42
```
You will then have something like:
```
$ ls ir-dumps
Standard.Base.Data.Filter_Condition.dot Standard.Base.Data.Time.dot Standard.Base.System.Advanced.dot Standard.Base.Warning.dot
Standard.Base.Data.Locale.dot Standard.Base.Enso_Cloud.Enso_File.dot Standard.Base.System.File.Advanced.dot tmp.dot
Standard.Base.Data.Numeric.dot Standard.Base.Errors.dot Standard.Base.System.File.dot
Standard.Base.Data.Numeric.Internal.dot Standard.Base.Network.HTTP.Internal.dot Standard.Base.System.File.Generic.dot
Standard.Base.Data.Text.Regex.Internal.dot Standard.Base.Runtime.dot Standard.Base.System.Internal.dot
```
You can then visualize any of these with `dot -Tsvg -O ir-dumps/tmp.dot`.
An example how that could look like is
The main culprit of a Vector slowdown (when compared to Array) was the normalization of the index when accessing the elements. Turns out that the Graal was very persistent on **not** inlining that particular fragment and that was degrading the results in benchmarks.
Being unable to force it to do it (looks like a combination of thunk execution and another layer of indirection) we resorted to just moving the normalization to the builtin method. That makes Array and Vector perform roughly the same.
Moved all handling of invalid index into the builtin as well, simplifying the Enso implementation. This also meant that `Vector.unsafe_at` is now obsolete.
Additionally, added support for negative indices in Array, to behave in the same way as for Vector.
# Important Notes
Note that this workaround only addresses this particular perf issue. I'm pretty sure we will have more of such scenarios.
Before the change `averageOverVector` benchmark averaged around `0.033 ms/op` now it does consistently `0.016 ms/op`, similarly to `averageOverArray`.
This PR adds sources for Enso language support in IGV (and NetBeans). The support is based on TextMate grammar shown in the editor and registration of the Enso language so IGV can find it. Then this PR adds new GitHub Actions workflow file to build the project using Maven.
