Metadata only
Datum
2023Typ
- Conference Paper
ETH Bibliographie
yes
Altmetrics
Abstract
Serverless computing is an emerging cloud paradigm that offers an elastic and scalable allocation of computing resources with pay-as-you-go billing. In the Function-as-a-Service (FaaS) programming model, applications comprise short-lived and stateless serverless functions executed in isolated containers or microVMs, which can quickly scale to thousands of instances and process terabytes of data. This flexibility comes at the cost of duplicated runtimes, libraries, and user data spread across many function instances, and cloud providers do not utilize this redundancy. The memory footprint of serverless forces removing idle containers to make space for new ones, which decreases performance through more cold starts and fewer data caching opportunities.We address this issue by proposing deduplicating memory pages of serverless workers with identical content, based on the content-based page-sharing concept of Linux Kernel Same-page Merging (KSM). We replace the background memory scanning process of KSM, as it is too slow to locate sharing candidates in short-lived functions. Instead, we design User-Guided Page Merging (UPM), a built-in Linux kernel module that leverages the madvise system call: we enable users to advise the kernel of memory areas that can be shared with others. We show that UPM reduces memory consumption by up to 55% on 16 concurrent containers executing a typical image recognition function, more than doubling the density for containers of the same function that can run on a system. Mehr anzeigen
Publikationsstatus
publishedExterne Links
Buchtitel
2023 IEEE International Conference on Big Data (Big Data)Seiten / Artikelnummer
Verlag
IEEEKonferenz
Thema
Serverless; Function-as-a-Service; Memory Deduplication; InferenceOrganisationseinheit
03950 - Hoefler, Torsten / Hoefler, Torsten
Förderung
101002047 - Productive Spatial Accelerator Programming (EC)
955606 - DEEP- Software for Exascale Archtiectures (EC)
955776 - Network Solution for Exascale Architectures (EC)
Zugehörige Publikationen und Daten
Is new version of: https://doi.org/10.48550/arXiv.2311.13588
ETH Bibliographie
yes
Altmetrics