Autor/s de la URV: | Barcelona Pons, Daniel / García López, Pedro Antonio |
Autor segons l'article: | Barcelona-Pons D; García-López P |
Adreça de correu electrònic de l'autor: | daniel.barcelona@urv.cat daniel.barcelona@urv.cat pedro.garcia@urv.cat |
Identificador de l'autor: | 0000-0002-6051-9424 0000-0002-6051-9424 0000-0002-9848-1492 |
Any de publicació de la revista: | 2021 |
Tipus de publicació: | Journal Publications |
Referència de l'ítem segons les normes APA: | Barcelona-Pons D; García-López P (2021). Benchmarking parallelism in FaaS platforms. Future Generation Computer Systems-The International Journal Of Escience, 124(), 268-284. DOI: 10.1016/j.future.2021.06.005 |
Referència a l'article segons font original: | Future Generation Computer Systems-The International Journal Of Escience. 124 268-284 |
Resum: | Serverless computing has seen a myriad of work exploring its potential. Some systems tackle Function-as-a-Service (FaaS) properties on automatic elasticity and scale to run highly-parallel computing jobs. However, they focus on specific platforms and convey that their ideas can be extrapolated to any FaaS runtime. An important question arises: do all FaaS platforms fit parallel computations? In this paper, we argue that not all of them provide the necessary means to host highly-parallel applications. To validate our hypothesis, we create a comparative framework and categorize the architectures of four cloud FaaS offerings, emphasizing parallel performance. We attest and extend this description with an empirical experiment that consists in plotting in deep detail the evolution of a parallel computing job on each service. The analysis of our results evinces that FaaS is not inherently good for parallel computations and architectural differences across platforms are decisive to categorize their performance. A key insight is the importance of virtualization technologies and the scheduling approach of FaaS platforms. Parallelism improves with lighter virtualization and proactive scheduling due to finer resource allocation and faster elasticity. This causes some platforms like AWS and IBM to perform well for highly-parallel computations, while others such as Azure present difficulties to achieve the required parallelism degree. Consequently, the information in this paper becomes of special interest to help users choose the most adequate infrastructure for their parallel applications. |
DOI de l'article: | 10.1016/j.future.2021.06.005 |
Enllaç font original: | https://www.sciencedirect.com/science/article/pii/S0167739X21001990?via%3Dihub |
Versió de l'article dipositat: | info:eu-repo/semantics/publishedVersion |
Accès a la llicència d'ús: | https://creativecommons.org/licenses/by/3.0/es/ |
Departament: | Enginyeria Informàtica i Matemàtiques |
URL Document de llicència: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
Àrees temàtiques: | Software Saúde coletiva Medicina ii Medicina i Matemática / probabilidade e estatística Interdisciplinar Hardware and architecture Engenharias iv Engenharias iii Engenharias i Comunicação e informação Computer science, theory & methods Computer networks and communications Ciências sociais aplicadas i Ciências biológicas ii Ciências biológicas i Ciência da computação |
Paraules clau: | Serverless Parallelism Faas Benchmark parallelism faas benchmark |
Entitat: | Universitat Rovira i Virgili |
Data d'alta del registre: | 2024-07-27 |
Pàgina inicial: | 268 |
Pàgina final: | 284 |
Volum de revista: | 124 |
Descripció: | Serverless computing has seen a myriad of work exploring its potential. Some systems tackle Function-as-a-Service (FaaS) properties on automatic elasticity and scale to run highly-parallel computing jobs. However, they focus on specific platforms and convey that their ideas can be extrapolated to any FaaS runtime. An important question arises: do all FaaS platforms fit parallel computations? In this paper, we argue that not all of them provide the necessary means to host highly-parallel applications. To validate our hypothesis, we create a comparative framework and categorize the architectures of four cloud FaaS offerings, emphasizing parallel performance. We attest and extend this description with an empirical experiment that consists in plotting in deep detail the evolution of a parallel computing job on each service. The analysis of our results evinces that FaaS is not inherently good for parallel computations and architectural differences across platforms are decisive to categorize their performance. A key insight is the importance of virtualization technologies and the scheduling approach of FaaS platforms. Parallelism improves with lighter virtualization and proactive scheduling due to finer resource allocation and faster elasticity. This causes some platforms like AWS and IBM to perform well for highly-parallel computations, while others such as Azure present difficulties to achieve the required parallelism degree. Consequently, the information in this paper becomes of special interest to help users choose the most adequate infrastructure for their parallel applications. |
Tipus: | Journal Publications |
Coautor: | Universitat Rovira i Virgili |
Títol: | Benchmarking parallelism in FaaS platforms |
Matèria: | Computer Networks and Communications,Computer Science, Theory & Methods,Hardware and Architecture,Software Serverless Parallelism Faas Benchmark parallelism faas benchmark Software Saúde coletiva Medicina ii Medicina i Matemática / probabilidade e estatística Interdisciplinar Hardware and architecture Engenharias iv Engenharias iii Engenharias i Comunicação e informação Computer science, theory & methods Computer networks and communications Ciências sociais aplicadas i Ciências biológicas ii Ciências biológicas i Ciência da computação |
Data: | 2021 |
Autor: | Barcelona-Pons D García-López P |
Drets: | info:eu-repo/semantics/openAccess |
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