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Communication Dans Un Congrès Année : 2022

CASY: A CPU Cache Allocation System for FaaS Platform

Résumé

Function as a Service (FaaS) has become a key service in the cloud. It enables customers to conceive their application as a collection of minimal serverless functions interacting with each other. FaaS platforms abstract all the management complexity to the client. This emerging paradigm is also attractive because of its billing model. Clients are charged based on the execution time of functions, allowing finer-grained pricing. Therefore, executing functions as fast as possible is very important to lower the cost. Several research studies have investigated runtime optimization in FaaS environments, but none have explored CPU cache allocation. Indeed, CPU cache contention is a well-known issue in software and FaaS is not exempt from this issue. Various hardware improvements have been made to address the CPU cache partitioning problem. Among other things, Intel has implemented a new technology in their new processors that allows cache partitioning: Cache Allocation Technology (CAT). This technology allows allocating cache ways to processes, and the usage of the cache by each process will be limited to the allocated amount. In this paper, we propose CASY (CPU Cache Allocation SYstem), a system that performs CPU cache allocation for serverless functions using the Intel CAT technology. CASY uses machine learning to build a cache usage profile for functions and uses this profile to predict the cache requirements based on the function's input data. Because the CPU's cache size is small, CASY integrates an allocation algorithm which ensures that the cache loads are balanced on all cache ways. We implemented our system and integrated it into the OpenWhisk FaaS platform. Our evaluations show a 11% decrease in execution time for some serverless functions without degrading the performance of other functions.

Domaines

Informatique
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Dates et versions

hal-03889808 , version 1 (08-12-2022)

Identifiants

Citer

Armel Jeatsa-Toulepi, Boris Teabe, Daniel Hagimont. CASY: A CPU Cache Allocation System for FaaS Platform. 22nd International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022), IEEE Computer Society; Technical Committee on Scalable Computing ACM SIGARCH, May 2022, Taormina, Italy. pp.494-503, ⟨10.1109/CCGrid54584.2022.00059⟩. ⟨hal-03889808⟩
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