SerPyTor: A distributed context-aware computational graph execution framework for durable execution

04/15/2023
by   Anuran Roy, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/09/2021

Context-Aware Task Handling in Resource-Constrained Robots with Virtualization

Intelligent mobile robots are critical in several scenarios. However, as...
research
02/22/2021

LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding

Knowledge graph embedding (KGE) models learn to project symbolic entitie...
research
08/27/2021

Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation

Distributed dataflow systems like Spark and Flink enable the use of clus...
research
12/06/2021

End-to-end Adaptive Distributed Training on PaddlePaddle

Distributed training has become a pervasive and effective approach for t...
research
01/28/2011

A Human-Centric Approach to Group-Based Context-Awareness

The emerging need for qualitative approaches in context-aware informatio...
research
08/30/2019

Internet-based Adaptive Distributed Simulation of Mobile Ad-hoc Networks

In this paper we focus on Internet-based simulation, a form of distribut...

Please sign up or login with your details

Forgot password? Click here to reset