  Distributed computation is always a tricky topic to deal with, especially in
context of various requirements in various scenarios. A popular solution is to
use Apache Spark with a setup of multiple systems forming a cluster. However,
the prerequisite setup for a Spark cluster often induces an additional
overhead, often limiting usage in constrained scenarios, especially in
scenarios requiring context propagation. In this paper, we explore a relatively
lightweight computational graph execution framework requiring little setup and
fast speeds, coupled with context awareness.
