[Language Request] Mojo by Modular
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- Dominant language
- JavaScript
- Stars
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- Merged PRs (30d)
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Description
Language
I'd like to add support for Mojo formally to Prism. I'm the lead frontend engineer at Modular and we already have a Prism definition we've been using.
We use Prism on our docsite, so you can see it in action here. We'd like to add it to upstream.
It's also supported in github too!
fn run_mandelbrot(parallel: Bool) raises -> Float64:
var matrix = Matrix[int_type, height, width]()
@parameter
fn worker(row: Int):
var scale_x = (max_x - min_x) / width
var scale_y = (max_y - min_y) / height
@parameter
fn compute_vector[simd_width: Int](col: Int):
"""Each time we operate on a `simd_width` vector of pixels."""
var cx = min_x + (col + iota[float_type, simd_width]()) * scale_x
var cy = min_y + row * scale_y
var c = ComplexSIMD[float_type, simd_width](cx, cy)
matrix.store(row, col, mandelbrot_kernel_SIMD[simd_width](c))
# Vectorize the call to compute_vector where call gets a chunk of pixels.
vectorize[compute_vector, simd_width](width)
@parameter
fn bench():
for row in range(height):
worker(row)
@parameter
fn bench_parallel():
parallelize[worker](height, height)
var time: Float64 = 0
if parallel:
time = benchmark.run[bench_parallel](max_runtime_secs=0.5).mean(unit)
else:
time = benchmark.run[bench](max_runtime_secs=0.5).mean(unit)
show_plot(matrix)
matrix.data.free()
return time
vectorized = run_mandelbrot(parallel=False)
print("Vectorized:", vectorized, unit)
Additional resources
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no repository files, tests, or entry points. Start by reviewing Prism's existing language definitions and the provided Mojo sample, then consult the Mojo Manual for syntax details; done means Mojo support is added upstream and the sample highlights correctly.
Written by the indexing model from the issue text.
Assessment
- Domain
- tooling
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100