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@ -197,31 +197,6 @@ in `R_INT_0` by `1`. In the "Locals" section, we can see that `R_INT_0` is the r
Eventually, Dust should be available via package managers and as an embeddable library. For now,
the only way to use Dust is to clone the repository and build it from source.
## Benchmarks
**Dust's runtime optimizations are still in development.**
See the `bench` directory for the benchmark programs.
### Addictive Addition
This benchmark was taken from a paper[^3] that compares stack-based and register-based virtual
machines. The benchmark is a simple program that increments a variable 5,000,000 times. Dust uses a
novel technique to improve loop performance. This optimization works by caching raw pointers to the
instruction's operand values so that they are only looked up during the first iteration of the loop
and then reused for the remaining iterations.
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:-------------------------------|-------------:|---------:|---------:|-------------:|
| `bun addictive_addition.js` | 10.7 ± 0.4 | 9.1 | 12.1 | 1.00 |
| `dust addictive_addition.ds` | 21.6 ± 0.5 | 20.5 | 22.8 | 2.02 ± 0.09 |
| `lua addictive_addition.lua` | 21.9 ± 0.2 | 21.8 | 23.3 | 2.05 ± 0.08 |
| `deno addictive_addition.js` | 24.4 ± 2.5 | 18.0 | 27.3 | 2.28 ± 0.24 |
| `node addictive_addition.js` | 44.7 ± 0.3 | 44.2 | 45.6 | 4.18 ± 0.15 |
| `ruby addictive_addition.rb` | 88.0 ± 23.6 | 75.8 | 219.7 | 8.23 ± 2.22 |
| `java addictive_addition.java` | 199.8 ± 4.8 | 195.8 | 209.4 | 18.69 ± 0.81 |
| `python addictive_addition.py` | 235.4 ± 27.1 | 216.9 | 322.9 | 22.02 ± 2.66 |
## Inspiration
*Crafting Interpreters*[^0] by Bob Nystrom was a great resource for writing the compiler, especially