Disaggregation and the Application

Abstract

This paper examines disaggregated data center architectures from the perspective of the applications that would run on these data centers, and challenges the abstractions that have been proposed to date. In particular, we argue that operating systems for disaggregated data centers should not abstract disaggregated hardware resources, such as memory, compute, and storage away from applications, but should instead give them information about, and control over, these resources. To this end, we propose additional OS abstractions and interfaces for disaggregation and show how they can improve data transfer in data parallel frameworks and speed up failure recovery in replicated, fault-tolerant applications. This paper studies the technical challenges in providing applications with this additional functionality and advances several preliminary proposals to overcome these challenges.

Transparent Serverless execution of Python multiprocessing applications

“…In [6], the authors propose to augment operating systems for disaggregation, by exposing explicitly the disaggregated resources to applications and thus opening efficient and optimized co-designs between applications and the remote resources.…”

“…The motivation of this paper is very simple: Low Latency ⇒ Disaggregation ⇒ Full Transparency. The downward trend in network latency [2,3] suggests that resource disaggregation is increasingly viable, which provides the opportunity to achieve access transparency in the next years [4,5,6]. Resource disaggregation in the Cloud has been the key to flexible scaling models provided by current serverless services such as Function-asa-Service (FaaS) or Object Storage.…”