Serverless Nanopore Basecalling with AWS Lambda

Grzesik, Piotr; Mrozek, Dariusz

doi:10.1007/978-3-030-77964-1_44

Cited by 6 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A new generation of platform-as-a-service products from significant cloud providers is referred to as "serverless computing. "Amazon Web Services (AWS) Lambda, the first service in this category, was introduced at the end of 2014 and had widespread usage in mid-to-late 2016 [9] by enabling workflows to run and scale without requiring human infrastructure management and providing support for highly parallel execution, it simplifies operations, abstracts away the underlying servers, and lowers maintenance costs [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing AWS lambda code execution time in amazon web services

Arifin,

Satra,

Syafie

et al. 2023

Bull.Socinf.The.App

View full text Add to dashboard Cite

One of the problems in providing infrastructure is the lack of interest in managing infrastructure. AWS Lambda is a FaaS (Function as a Service) service that allows users to run code automatically in an environment managed by Amazon Web Services. In this study, the method used is to collect data on code execution time at various input sizes, then perform an analysis of the factors that affect execution time. Furthermore, optimization is carried out by selecting the appropriate memory size and proper coding techniques to improve performance. The results show that optimizing memory size and coding can improve code execution time performance by up to 30%, depending on the type of service used. This can help AWS Lambda users improve code performance and save on operational costs.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Optimizing AWS lambda code execution time in amazon web services

Arifin,

Satra,

Syafie

et al. 2023

Bull.Socinf.The.App

View full text Add to dashboard Cite

show abstract

“…To evaluate the different services, i.e., AWS Lambda, GCF, and GCR wrt the performance of parallelized functions, we chose multiple programming languages, i.e., C++, Go, and Java. We chose C++ since it is widely used for scientific computing in high performance computing applications [14]. However, none of the major commercial FaaS platforms support C++ by default.…”

Section: Language Runtimesmentioning

confidence: 99%

“…With the advent of Amazon Web Services (AWS) Lambda in 2014, serverless computing has gained popularity and more adoption in different application domains such as machine learning [6,7,15], scientific computing [9,14,16,17], and linear algebra [31]. In serverless computing, developers do not have to manage infrastructure themselves but completely hand over this responsibility to a Function-as-a-Service Platform.…”

Section: Introductionmentioning

confidence: 99%

Towards Demystifying Intra-Function Parallelism in Serverless Computing

Kiener¹,

Chadha²,

Gerndt³

2021

Preprint

View full text Add to dashboard Cite

Serverless computing offers a pay-per-use model with high elasticity and automatic scaling for a wide range of applications. Since cloud providers abstract most of the underlying infrastructure, these services work similarly to black-boxes. As a result, users can influence the resources allocated to their functions, but might not be aware that they have to parallelize them to profit from the additionally allocated virtual CPUs (vCPUs). In this paper, we analyze the impact of parallelization within a single function and container instance for AWS Lambda, Google Cloud Functions (GCF), and Google Cloud Run (GCR). We focus on compute-intensive workloads since they benefit greatly from parallelization. Furthermore, we investigate the correlation between the number of allocated CPU cores and vCPUs in serverless environments. Our results show that the number of available cores to a function/container instance does not always equal the number of allocated vCPUs. By parallelizing serverless workloads, we observed cost savings up to 81% for AWS Lambda, 49% for GCF, and 69.8% for GCR.CCS Concepts: • Computer systems organization → Cloud computing.

show abstract

Accelerating Edge Metagenomic Analysis with Serverless-Based Cloud Offloading

Grzesik,

Mrozek

2022

Computational Science – ICCS 2022

View full text Add to dashboard Cite

Serverless Nanopore Basecalling with AWS Lambda

Cited by 6 publications

References 13 publications

Optimizing AWS lambda code execution time in amazon web services

Optimizing AWS lambda code execution time in amazon web services

Towards Demystifying Intra-Function Parallelism in Serverless Computing

Accelerating Edge Metagenomic Analysis with Serverless-Based Cloud Offloading

Contact Info

Product

Resources

About