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Fix broken link for 24.11
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shriram-jagan committed Nov 20, 2024
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# Legate Sparse

Legate Sparse is a [Legate](https://github.com/nv-legate/legate.core) library
Legate Sparse is a [Legate](https://github.com/nv-legate/legate) library
that aims to provide a distributed and accelerated drop-in replacement for the
[scipy.sparse](https://docs.scipy.org/doc/scipy/reference/sparse.html) library
on top of the [Legate](https://github.com/nv-legate/legate.core) runtime.
on top of the [Legate](https://github.com/nv-legate/legate) runtime.
Legate Sparse interoperates with
[cuPyNumeric](https://github.com/nv-legate/cupynumeric/tree/main),
[cuPyNumeric](https://github.com/nv-legate/cupynumeric),
a distributed and accelerated drop-in replacement
for [NumPy](https://numpy.org/doc/stable/reference/index.html#reference), to
enable writing programs that operate on distributed dense and sparse arrays.
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To use Legate Sparse, `legate` and `cupynumeric` libraries have to be installed.
They can be installed either by pulling the respective conda packages
or by manually building from source. For more information,
see build instructions for [Legate](https://github.com/nv-legate/legate.core)
and [cuPyNumeric](https://github.com/nv-legate/cupynumeric/tree/main).
see build instructions for [Legate](https://github.com/nv-legate/legate)
and [cuPyNumeric](https://github.com/nv-legate/cupynumeric).

Follow the steps in this section.

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and not `legate.sparse`. Here is an example program saved as `main.py`.

For more details on how to run legate programs, check
our [documentation](https://docs.nvidia.com/cupynumeric/24.06/).
our [documentation](https://docs.nvidia.com/cupynumeric).
To run the application on a single GPU, use this command:

`legate --gpus 1 ./main.py`
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