Assessment of High Performance Computing

Services Potential of SMEs

M. Kljajić Borštnar*, T. Ilijaš ** * University of Maribor, Faculty of Organizational Sciences/Department of Informatics, Kranj, Slovenia

** Arctur, d.o.o., Nova Gorica, Slovenia

mirjana.kljajic@fov.uni-mb.si, tomi.ilijas@arctur.si

Abstract - High Performance Computing (HPC) enables

solving complex problems that would be otherwise

impossible to compute with ordinary desktop computers in

an acceptable time. HPC services, offered in cloud, could

foster new products and/or services development, faster

time to market and optimization of production processes for

Small and Medium sized enterprises (SME). However, cloud

HPC services adoption among SMEs is still scarce and not

all SMEs are viable to use HPC. The goal was to assess the

cloud HPC potential among SMEs, select the viable SMEs

and support them in implementation of the technology. For

this purpose we have developed a web-based multi-criteria

assessment tool to measure the potential of the SMEs to use

cloud HPC services. In this paper we present the analysis of

the 61 assessed organizations, among which 38 were SMEs.

The analysis offers a limited insight into the state of the

European SMEs and other organizations, but is important

for understanding the needs and opportunities, that the

cloud HPC services offer.

Keywords – High Performance Computing; Cloud

computing; Potential assessment; SME

I. INTRODUCTION

High Performance Computing (HPC) refers to computing performance needed for solving complex computing problems that could not easily (or timely) be computed by typical desktop computers. It is generally used for solving large scale problems in science, engineering and business [1]. So far HPC was mainly reserved for the large companies and research institutes, who could afford high costs that are associated with HPC. From the industry perspective the HPC is predominantly used in manufacturing sector with financial sector just behind it [2]. On the other hand, adoption of cloud computing services is high among companies, including SMEs [3], therefore there is an opportunity to make HPC services available in the cloud and thus make it affordable for the SMEs [4]. However, adoption of HPC services in the cloud is still weak [5]. The problems lie not merely in the price, but also in the lack of knowledge, and competences that are needed to first identify the potential and then know how to use HPC. An important step is being made in the sense of identifying the potential uses of HPC, transformation power that it has in the sense of business models for the whole business ecosystem (companies, ISV, HPC infrastructure providers, experts etc). Cloud HPC service does not encompass only IaaS,

but includes also modeling services, software adaptation (parallelization), implementation and maintenance. The business models need to be changed from the existing IaaS, PaaS and SaaS to a more elastic approach to providing licensing (from classical licensing to adaptable pay per use licensing according to the actual needs), furthermore there is a need for a “Simulation Workflow as a Service”, that would be accessible through a »one-stop-shops«, as are being developed and tested in the EU project Fortissimo [6]. These kinds of holistic services can become of interest to other industrial segments, also for the SMEs [7]. More precisely, the European Commission roughly assesses that the manufacturing SMEs would benefit best from the cloud HPC services. They represent about 2 million SMEs (of the whole 24,5 SMEs) [8].

A. SME sector in the EU

According to Annual SME Report [8], in 2017 there were 24,6 million SMEs registered in the EU countries, 22,9 million of those were micro, 1,4 million small, and 0,2 million medium sized enterprises. In total the SME sector is accounted for 4.156 billion EUR added value, and employs 94,8 million people in the non-financial sector. In other words, SMEs employ two thirds of population and generate 56,8% of the entire added value of non-financial sector. Between 2013 and 2017 the SME sector recorded 7,1% employment growth, added value increased by 15,1%. Both, large companies and SMEs have surpassed the financial indicators from 2008, but not in all EU member states. There is also a significant gap between large and SME sector, especially due to weak internationalization among the SMEs. SMEs can be found in all industrial sectors, nevertheless medium SMEs are more internationally oriented compared to small and micro companies.

Similarly to internationalization, SMEs lag behind in the field of digital transformation. They have adopted basic digital business support technologies (ERP, social media etc.), but are lagging behind with adoption of advanced digital technologies (i.e. robotics, internet of things, big data & analytics, block chain, artificial intelligence) [9]. European commission has specifically stressed the importance of cloud and HPC technologies in communication »European Cloud Initiative – Building the competitive data and knowledge economy in Europe« [10]. The initiative sets out to provide a European scientific, industrial and public organizations data infrastructure for storing and managing data, fast

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connectivity and data transfer, and HPC for data processing by the year 2020. Return on investment of HPC is very high, meaning every invested euro yields on average 867 EUR of revenue and 69 EUR in profit. EU is in fact leading in the use of HPC resources, but currently owns no so called supercomputer that is among top 10 in the world. While possessing only 5% of all HPC resources, EU currently consumes one third of the world’s HPC resources [11]. Therefore, one of the main goals is to set up an EU HPC infrastructure for EU research, industry and other organizations. In September 2018 the European parliament supported the “EURO HPC JU” (euorhpc.eu) initiative for setting up an »exa-scale« supercomputer (by 2022/23).

In parallel to the infrastructure investment and development, there are lots of activities on the forefront of HPC services offered in cloud [12, 13]. On the European level, within the initiative »ICT Innovation for Manufacturing SMEs« (i4MS), which main goal is to support manufacturing SMEs in adoption of key enabling technologies, funding is available to develop and test possibilities for cloud HPC services. Manufacturing SMEs are specifically identified as the ones that could benefit most from digitalization, especially by “cloudifying engineering services, by combining HPC resources, computational tools, and cloud computing platforms” [14]. Through the i4MS initiative European Commission supports the following four key areas: robotics, cloud HPC simulation services, laser technology applications, and intelligent sensor-based equipment. By developing and supporting new business ideas, particularly the use of HPC services in manufacturing SMEs, the initiative aims to foster the new economic growth and competitiveness by reducing development times for innovative products with better performance. The results of these initiatives are fostering engineering and the processes of prototyping within the manufacturing workflow. In previous experiments we haven’t seen the desired results from an integrated information workflow and simulation loop based on online factory data though [14].

An important part of the i4MS funds are invested in adoption of cloud HPC services by selecting experiments for showcasing the best practices, develop, test and demonstrate the use of infrastructure and the business model as a “one-stop pay-per-use shop” [6]. Experiments include all actors (SME, Innovation centers/clusters, experts, code providers) throughout the value chain of an innovation ecosystem (in projects like for example CloudFlow, Fortissimo, Cloudifactory). One of the important goals of the initiative is the “development of a sustainable business model, which is crucial for the successful adoption of these services” [15]. Therefore, general criteria for selection of an experiment are: demonstration of HPC needs for new product development in manufacturing industry; end-user driven, address a real use-case, and demonstrate the use of HPC and high potential to benefit from cloud technology [16].

For the purpose of assessing potential to use the cloud HPC services, we have developed a multiple-criteria model based on multiple criteria decision analysis MCDA [17] and validate it on a set of experiments, conducted in CloudFlow, Fortissimo, and Fortissimo II projects. Within

the Sesame project the web questionnaire was developed to elicit knowledge from the SMEs (HPC4SME assessment tool). To this date there were over 90 experiments conducted in the CloudFlow, Fortissimo, Fortissimo II projects, and over 60 SMEs potential assessed with the HPC4SME assessment tool, set up within the Sesame project. Main goals of the project were selecting appropriate SMEs who could benefit from the cloud HPC services, raise the awareness of the HPC technology among manufacturing SMEs by showcasing the successful experiments, and set up the central access point to HPC services and thus enlarge the HPC market.

Aim of this paper is to present the analysis of 61 organizations that have completed the online assessment. Special focus of analysis will be put on the 40 SMEs. The insights will enable us to define the further research steps, assess the quality of the questionnaire and answer the following research question: Are European small and medium sized enterprises ready to take on the cloud HPC services? We believe that this research will contribute to identification of SMEs who could benefit by using cloud HPC services, identify the main obstacles to cloud HPC services adoption, and provide policy implications for SMEs adoption of digital technologies, like HPC, big data analytics, artificial intelligence, internet of things etc.

II. RESEARCH METHODOLOGY

The general approach, used in this research, is a mixed strategy of design science research [18] and survey, described in Figure 1.

2MIO SMEs Selected SMEs

Problem definitionResearch QuestionEvaluation Criteria

DEX methodologyModel

development

Research questino answer

Contribution to new knowledge

Design

Relevance Rigor

Assessment Model

Online Question

aire

Assessed Potential

Success Stories

SMEs

Figure 1. Research framework

As shown in Figure 1 in the first step of research we have developed the multi-criteria assessment model using design science research approach. The main goal is to develop an IT artefact (construct, model, prototype, instantiation) that will demonstrate practical relevance, and is fundamentally rooted in problem-solving paradigm [18]. In our case the IT artefact is a qualitative multi-criteria model that we have developed using DEX methodology [19] and was tested on experiments conducted in the CloudFlow project. In the second phase we designed a questionnaire by which we could elicit data from the SMEs. The questionnaire was tested with the companies already collaborating in the experiments of Fortissimo projects. The questionnaire was made available online and during the second part of 2017. To date we

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have engaged 61 organizations to assess their cloud HPC potential.

A. Instrument and Data Collection

methods

Predominantly the manufacturing SMEs were targeted through various media outlets (i.e. project partners and their dissemination activities, conferences, workshops, LinkedIn, Twitter, and Facebook), but anyone who wished to assess their potential was welcome. A feedback was provided to each registered respondent in the form of a detailed report on their current and future cloud HPC potential. The main data gathering method was online questionnaire (HPC4SME Assessment Tool, network.sesame.net), which consisted of 32 questions, divided into three sections: 1) Readiness, with this group of questions we tried to get understanding about the current state of knowledge and adoption of HPC services in organization; 2) Cloud, this group of questions provides insights in understating and experiences of cloud technologies and services; and 3) HPC, which refers to a group of questions assessing computational needs, understanding and experiences with HPC. Since questions can be difficult to understand, each question is further explained and an option of “ask an expert” is available. Questions are measured on the discrete qualitative scale that is directly connected to the multiple-criteria model. Top level of the model is presented in Figure 2. For example, to a question »How would you rate the applicability of simulation in your sector?« respondents could have selected one of the suggested answers: »Great Potential«, »Applicable« in »Not Applicable«. The scales are descriptive in order to be easy to understand, and ordered from less desirable to most desirable value (i.e. “Not Applicable”, “Applicable”, “Great Potential”).

Figure 2. Top Level of multiple-criteria assessment model

The multiple-criteria model was developed on the basis of experiments in the CloudFlow and Fortissimo projects, and had been updated several times. Details on the multiple-criteria assessment model development can be found in [17].

B. Data Analysis

Data were collected through an online questionnaire and exported to DEXi multi-criteria model [17] to assess the cloud HPC potential. The model consisted of 32 basic criteria (that corresponded to 32 questions in the questionnaire) and 21 aggregated criteria. Evaluation was conducted using the DEXi methodology which assumes deriving the aggregated criteria by using the criteria function defined as a set of simple “if-then” rules [19].

The final values are thus derived from lower laying criteria values in line with the defined criteria function. The final value can be assessed even with missing values and provide transparent reasoning of every derived criteria value. When all aggregated criteria had been calculated, the values of all the 61 organizations can be analyzed.

III. RESULTS

Analysis is based on the 61 organizations, who filled in the assessment questionnaire voluntarily. Among the assessed organizations there were 62% of SMEs, 16% of large enterprises, 1% of research institutes, the rest are universities, associations, competence centers and government institutions. We have followed the current EU recommendation [20] for size of the company, by which all the large companies in our samples just fall outside the SME definition. However, the companies that can afford own HPC infrastructure are usually very large companies, research institutes and government institutions. On the other hand, those companies are the ones that would potentially benefit from the services greatly, therefore we are including them in the analysis but report the results separately. The main limitation of the research is the sample, which offers only limited insights into the state of cloud HPC potential among European SMEs. The fact that we have managed to engage only 38 SMEs shows that awareness among that population is still very low.

Majority of organizations originate in Slovenia, Serbia, Bulgaria, following by Spain and Greece, Germany, United Kingdom and Croatia, Poland, Italy, Austria, France, Norway, North Macedonia, Israel and Ireland (Figure 3).

0 2 4 6 8 10 12 14 16 18

Slovenia

Serbia

Bolgaria

Spain

Greece

Germany

UK

Croatia

Poland

Italy

Austria

France

Norway

Portugal

Macedonia

Israel

Ireland

Figure 3. Assessed organizations by the country

In Figure 4 we present the distribution of cloud HPC potential assessment for all organizations, SMEs and large companies. Nearly 40% of all organizations were assessed as “Magic quadrant – Ready”, 36% organizations were assessed as having “Low potential” to use cloud HPC services, 24% are assessed to be “Close to Magic Quadrant”. Regarding the SMEs alone, about half are assessed as “Magic quadrant – ready”, what means that they could immediately benefit from using cloud HPC. Two of the assessed SMEs are not ready to use the services yet, seven are considered to be close to the “Magic quadrant” and 11 have “Low potential” of using

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the services. Only two (out of ten) large companies are assessed to be ready to use cloud HPC services, the rest are low potential of close to magic quadrant.

0 20 40 60 80 100

Magic Quadrant - Ready

Low Potential

Close to Magic Quadrant

Magic Quadrant - Not ready yet

Large SME All

Figure 4. Cloud HPC Potential assessment for all 61 organizations, 40

SMEs and Large companies

Analysis of internal and external organizational factors are presented by the aggregated criteria “Readiness”, according to the analysis, most organizations (70%) are ready to take upon new business opportunities. 77% of organizations had identified HPC opportunities within their sector, 68% reported their organizations to be ready to take on HPC. There is no difference between the types of organization (SME, large, institution, etc.).

Further we analyzed the potential to use HPC (Y axis) in the cloud (X axis) (Figure 5). Both aggregated criteria were assessed on a four level scale (»No potential«, »Low potential«, »Fair potential«, »High potential«). Each point in Figure 5 represent individual SME, the color of the point represents the overall assessment (orange – Magic quadrant – ready, green – Magic quadrant – not ready yet, blue – Close to magic quadrant, and red – Low potential).

Figure 5. HPC and Cloud assessment for SMEs

According to responses, overall 70% of all responding organizations could access HPC services through cloud, and as much as 13% of them cannot use cloud to consume those services (due to various reasons: complex simulation processes, confidentiality of data and/or results). Assessment of possibility to use the cloud environment for the SMEs revealed that 60% have high cloud potential,

5% fair, 35% low or no cloud potential. Regarding computational needs and possibilities to employ HPC, 45% of SMEs are assessed as “High potential”, 21% of SMEs as having “Fair potential”, 34% as low or no potential. Comparing to overall assessed organizations, the SMEs, who took part in the study, show higher potential for using cloud HPC services.

IV. CONCLUSION

In this paper we addressed the problem of assessing the cloud HPC potential of European SMEs. The availability of high-performance computing for SMEs is crucial for new product and/or service development, competitiveness and economic growth. Unfortunately the readiness of this sector to adopt high-end digital technologies, like HPC, is still weak. EU is putting a lot of effort in making sector of manufacturing SMEs aware of the benefit of digital technologies. One of the problems is to identify those SMEs who could benefit from using HPC services and support them in the process of HPC implementation and business model transformation. For this purpose we have developed an online survey, which provides an input data to the multi-criteria assessment model, implemented in DEXi program. By HPC4SMEs Assessment Tool we can identify the current potential of a specific SME and analyze its future potential. Furthermore, the collected data provide an important insight into the state of European SMEs regarding the ability to use cloud HPC services.

In the paper we have presented the assessment of the main three groups of criteria (readiness, HPC and Cloud) and the overall cloud HPC potential assessment. In spite of huge engagement of project partners, we have to date acquired only 61 responses, 38 of which were SMEs. These organizations have not previously been involved in projects, but had already been aware of HPC benefits. This study had revealed that SMEs in general are not yet familiar with the potential of cloud HPC services, which is corroborated by the fact that only 38 of SMEs from across the EU took part in the assessment, and only half of those were assessed to have potential of using the services.

The limitation of the study is the small sample of SMEs, which is a good indicator that in the future we need to be doing a lot more to raise the awareness among them. Interestingly, 21 other organizations took part in the assessment, which shows that organizations, such as large companies, universities, associations, and institutes are interested in cloud HPC services as well.

In the future we will conduct another round of European survey, by which we plan to reach a larger number of SMEs. This will give us a better insight into what kind of strategies we need to take in order to better prepare the European market for the opportunities offered by digital technologies.

ACKNOWLEDGMENT

This research was partly funded by research program P5-0018, Slovenian Research Agency, and EU Horizon 2020 project Sesame, Grant Agreement No 654416. We are grateful to all the project partners, who were

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cooperating in collecting data and testing the multi-criteria model.

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