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Run One Program at any Scale with Legate
legate.numpy
The Legate core provides the building blocks for other Legate Python modules. The main one is NumPy on top of Legate, or legate.numpy , which implements some NumPy functions with the goal of someday implementing all of them. At the time of this writing, it supports the following data types: float16 , float32 , float64 , int16 , int32 , int64 , uint16 , uint32 , uint64 , bool , complex64 , and complex128 . Legate currently only works on up to three-dimensional arrays but in time should support n -dimensional arrays.
Building legate.numpy is not difficult. As the rootuser, use the command,
# python setup.py --with-core /usr/local/legate
which installs legate.numpy where legate.core is located.
A Legate module for Pandas, legate.pandas , is being developed, but I didn’t build or test it for this article, although it should not be difficult to build or use.
Testing legate.numpy
Getting started with Legate is very easy. You do not run your Python code with python3 code.py ; rather, you use legate code.py . For your NumPy code to run normally, it needs to important legate.numpy first:
import legate.numpy as np
Legate in default mode is in this case just for a single node. As I built it, Legate defaults to four cores (the system has four cores, eight with hyperthreading turned on) with GPU support.
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