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NOTE: Legate Sparse is currently in an experimental state and not production quality

Legate Sparse

Legate Sparse is a Legate library that aims to provide a distributed and accelerated drop-in replacement for the scipy.sparse library on top of the Legion runtime. Legate Sparse interoperates with cuNumeric to enable writing programs that operate on distributed dense and sparse arrays. For some examples, take a look at the examples/ directory. We have implemented a PDE Solver, as well as Geometric and Algebraic multi-grid solvers using Legate Sparse. More complex and interesting applications are on the way -- stay tuned!

Building

To use Legate Sparse, you must build Legate and cuNumeric from source. In particular, the following branch of Legate and the following branch of cuNumeric must be used as many necessary changes have not yet made their way into the main branches of Legate and cuNumeric.

Instructions

First, clone quickstart and checkout the legate-sparse branch. This repository contains several scripts to cover common machines and use cases. Then, clone legate.core and cuNumeric, and check out the legate-sparse branch of each, provided by the following forks: legate.core, cuNumeric. Then, clone Legate Sparse. We recommend the following directory organization:

legate/
  quickstart/
  legate.core/
  cunumeric/
  legate.sparse/

Second, set up a conda environment:

quickstart/setup_conda.sh

Running ./quickstart/setup_conda.sh --help will display different options that allow you to customize the created conda installation and environment.

Third, install legate.core:

cd legate.core/
git clone https://gitlab.com/StanfordLegion/legion/
cd legion && git checkout control_replication && cd ../
LEGION_DIR=legion ../quickstart/build.sh

Fourth, install cunumeric:

cd cunumeric/
../quickstart/build.sh

Finally, install legate.sparse:

cd legate.sparse
../quickstart/build.sh

The quickstart/build.sh script will attempt to auto-detect the machine you are running on, if it is a common machine that the Legate or Legion developers frequently use. Otherwise, it will ask for additional information to be specified, such as the GPU architecture or network interconnect.

Usage

To write programs using Legate Sparse, import the sparse module, which contains methods and types found in scipy.sparse.

import sparse.io as io
mat = io.mmread("testdata/test.mtx").tocsr()
print((mat + mat).todense())
"""
[[4. 0. 0. 6. 0.]
 [0. 0. 0. 0. 8.]
 [0. 0. 0. 0. 0.]
 [6. 0. 0. 0. 0.]
 [0. 8. 0. 0. 0.]]
"""