Mars is a tensor-based unified framework for large-scale data computation.

Mars tensor


Mars tensor provides a familiar interface like Numpy.

Numpy Mars tensor
import numpy as np
a = np.random.rand(1000, 2000)
(a + 1).sum(axis=1)
import mars.tensor as mt
a = mt.random.rand(1000, 2000)
(a + 1).sum(axis=1).execute()

Easy to scale in and scale out

Mars can scale in to a single machine, and scale out to a cluster with hundreds of machines. Both the local and distributed version share the same piece of code, it’s fairly simple to migrate from a single machine to a cluster due to the increase of data.