BalticLSC: Low-Code Software Development Platform for Large Scale Computations

Marek, Krzysztof; Śmiałek, Michał; Rybiński, Kamil; Roszczyk, Radosław; Wdowiak, Marek

doi:10.31577/cai_2021_4_734

Cited by 9 publications

(4 citation statements)

References 12 publications

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“…Loading Docker containers at each execution causes much higher costs than function calls, so the containers are often cached and used repeatedly. The FaaS paradigm is also well suited for low-code [3] programming, as the serverless concept frees the developer of a whole class of details (code and data location, connections, etc. ).…”

Section: The Function As a Service Paradigmmentioning

confidence: 99%

Architecture of a Function-as-a-Service Application

Habala,

Bobák,

Šeleng

et al. 2023

cai

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Serverless computing and Function-as-a-Service (FaaS) are programming paradigms that have many advantages for modern, distributed and highly modular applications. However, the process of transforming a legacy, monolithic application into a set of functions suitable for a FaaS environment can be a complex task. It may be questionable whether the obvious advantages received from such a transformation outweigh the effort and resources spent on it. In this paper we present our continuing research aimed at the transformation of legacy applications into the FaaS paradigm. Our test subject is an airport visibility system, a sub-class of the meteorological services required for airport operations. We have chosen to modularize the application, divide it into parts that can be implemented as functions in the FaaS paradigm, and provide it with a simple cloud-based data management layer. The tools that we are using are Apache OpenWhisk for FaaS and Airflow for workflow management, Apache Airflow for workflow management and NextCloud for cloud storage. Only a part of the original application has been transformed, but it already allows us to draw some conclusions and especially start forming a generalized picture of a Function-as-a-Service application.

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Section: The Function As a Service Paradigmmentioning

confidence: 99%

Architecture of a Function-as-a-Service Application

Habala,

Bobák,

Šeleng

et al. 2023

cai

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“…Cost prediction can be facilitated if the computation algorithms are implemented in a modularized and standardized form. Such an approach is taken in the Baltic Large Scale Computing system (BalticLSC [1,2], https:// www.balticlsc.eu). It uses a visual language, called the Computation Application Language (CAL), to define datadriven computation applications.…”

Section: Contextmentioning

confidence: 99%

Estimation of execution time for computing tasks

Bielecki

Śmiałek

2022

Cluster Comput

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This work aims to estimate the execution time of data processing tasks (specific executions of a program or an algorithm) before their execution. The paper focuses on the estimation of the average-case execution time (ACET). This metric can be used to predict the approximate cost of computations, e.g. when resource consumption in a High-Performance Computing system has to be known in advance. The presented approach proposes to create machine learning models using historical data. The models use program metadata (properties of input data) and parameters of the run-time environment as their explanatory variables. Moreover, the set of these variables can be easily expanded with additional parameters of the specific programs. The program code itself is treated as a black box. The response variable of the model is the execution time. The models have been validated within a Large-Scale Computing system that allows for a unified treatment of programs as computation modules. We present the process of training and validation for several different computation modules and discuss the suitability of the proposed models for ACET estimation in various computing environments.

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“…In a data flow-driven approach to LSC, computation applications are divided into computation steps, with data flowing as messages between these steps. An example of such a system is the Balti-cLSC platform [18], [13] (www.balticlsc.eu). It is a low-code computation environment created as part of a project intended to facilitate easier access to LSC.…”

Section: Introductionmentioning

confidence: 99%

Multi-queue service for task scheduling based on data availability

Rybiński,

Śmiałek

2023

Annals of Computer Science and Information Systems

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Large-scale computation (LSC) systems are often performed in distributed environments where message passing is the key to orchestrating computations. In this paper, we present a new message queue concept developed within the context of an LSC system (BalticLSC). The concept consists in proposing a multi-queue, where queues are grouped into families. A queue family can be used to distribute messages of the same kind to multiple computation modules distributed between various nodes. Such message families can be synchronised to implement a mechanism for initiating computation jobs based on multiple data inputs. Moreover, the proposed multi-queue has built-in mechanisms for controlling message sequences in applications where complex data set splitting is necessary. The presented multi-queue concept was successfully implemented and applied in a working LSC system.

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BalticLSC: Low-Code Software Development Platform for Large Scale Computations

Cited by 9 publications

References 12 publications

Architecture of a Function-as-a-Service Application

Architecture of a Function-as-a-Service Application

Estimation of execution time for computing tasks

Multi-queue service for task scheduling based on data availability

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