FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC

Spillner, Josef; Mateos, Cristian; Monge, David A.

doi:10.1007/978-3-319-73353-1_11

Cited by 48 publications

(33 citation statements)

References 5 publications

(3 reference statements)

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“…Continuum services can be defined as microservices 1 [18], as they are small and modular, communicate through lightweight mechanisms (often through an HTTP RESTful API), and are independently deployable by fully automated machinery. Moreover, continuum μ-services are aligned with the Function-as-a-Service (FaaS) execution model [29]. FaaS has been proposed as an alternative cloud paradigm in which business functionality 2 is provided without preallocating computational resources.…”

Section: Application Modelmentioning

confidence: 99%

A Unified Model for the Mobile-Edge-Cloud Continuum

Baresi

Mendonça

Garriga

et al. 2019

ACM Trans. Internet Technol.

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Technologies such as mobile, edge, and cloud computing have the potential to form a computing continuum for new, disruptive applications. At runtime, applications can choose to execute parts of their logic on different infrastructures that constitute the continuum, with the goal of minimizing latency and battery consumption and maximizing availability. In this article, we propose A3-E, a unified model for managing the life cycle of continuum applications. In particular, A3-E exploits the Functions-as-a-Service model to bring computation to the continuum in the form of microservices. Furthermore, A3-E selects where to execute a certain function based on the specific context and user requirements. The article also presents a prototype framework that implements the concepts behind A3-E. Results show that A3-E is capable of dynamically deploying microservices and routing the application's requests, reducing latency by up to 90% when using edge instead of cloud resources, and battery consumption by 74% when computation has been offloaded.

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Section: Application Modelmentioning

confidence: 99%

A Unified Model for the Mobile-Edge-Cloud Continuum

Baresi

Mendonça

Garriga

et al. 2019

ACM Trans. Internet Technol.

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“…Their results indicate a lack of benchmarks that observe functions not in an isolated but in a shared environment of a Cloud Service. Spillner et al (2017) analyze several resourceintensive tasks in terms of comparing FaaS models with conventional monolithic algorithms. The authors conduct several experiments and compare the performance and other resource-related characteristics.…”

Section: Related Workmentioning

confidence: 99%

Function-as-a-Service Benchmarking Framework

Pellegrini¹,

Ivkic

Tauber

2019

Proceedings of the 9th International Conference on Cloud Computing and Services Science

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Cloud Service Providers deliver their products in form of "as-a-Service", which are typically categorized by the level of abstraction. This approach hides the implementation details and shows only functionality to the user. However, the problem is that it is hard to measure the performance of Cloud services, because they behave like black boxes. Especially with Function-as-a-Service it is even more difficult because it completely hides server and infrastructure management from users by design. Cloud Service Prodivers usually restrict the maximum size of code, memory and runtime of Cloud Functions. Nevertheless, users need clarification if more ressources are needed to deliver services in high quality. In this regard, we present the architectural design of a new Function-as-a-Service benchmarking tool, which allows users to evaluate the performance of Cloud Functions. Furthermore, the capabilities of the framework are tested on an isolated platform with a specific workload. The results show that users are able to get insights into Function-as-a-Service environments. This, in turn, allows users to identify factors which may slow down or speed up the performance of Cloud Functions.

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“…Recent research sheds some light on the challenges associated with this service model. For instance, in contrast to virtual machines it is not possible to provision resource-differentiated function instance types in commercial services [14].…”

Section: Serverless Foundationsmentioning

confidence: 99%

Practical Tooling for Serverless Computing

Spillner

2017

Proceedings of The10th International Conference on Utility and Cloud Computing

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Cloud applications are increasingly built from a mixture of runtime technologies. Hosted functions and service-oriented web hooks are among the most recent ones which are natively supported by cloud platforms. They are collectively referred to as serverless computing by application engineers due to the transparent on-demand instance activation and microbilling without the need to provision infrastructure explicitly. This half-day tutorial explains the use cases for serverless computing and the drivers and existing software solutions behind the programming and deployment model also known as Function-as-a-Service in the overall cloud computing stack. Furthermore, it presents practical open source tools for deriving functions from legacy code and for the management and execution of functions in private and public clouds. CCS CONCEPTS· Networks → Cloud computing; · Software and its engineering → Automatic programming; Software as a service orchestration system;

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FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC

Cited by 48 publications

References 5 publications

A Unified Model for the Mobile-Edge-Cloud Continuum

A Unified Model for the Mobile-Edge-Cloud Continuum

Function-as-a-Service Benchmarking Framework

Practical Tooling for Serverless Computing

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