We are a team of professionals, able to offer innovative information technology solutions to your business. We can also offer supercomputer resources, that do not have analogues in Lithuania, various specialized software, large amount data management, analysis, modelling and simulation services, as well as expertise services. Our passion is looking for solutions, therefore, if you have an idea, we will be pleased to implement it!
We aim to:
- make supercomputer resources easily accessible
- develop grid and cloud computing technologies
- create an attractive computing and service center
We can offer scientific research and experimental development in:
- Informatics engineering
Advantages for you:
Supercomputer is a very powerful computer, which can process large amounts of information and perform calculations for modelling complex processes such as nuclear reactions and biochemical processes or even customers' habits. Using these resources scientists and business representatives can shorten calculation time many times and get more accurate results.
IT Research center was established based on Senate Resolution No. S-2010-06-30 and EU structural support project VP2-1.1-MES-04-V-01-002 "Information technology research center establishment". IT Research center operates as a research laboratory and it is focused on education, research and business.
We provide the following services:
Creation of data analysis models in HPC environment. Initiation of data analysis process; data preparation for data analysis; development and experimental evaluation of algorithms suitable for data analysis. Algorithms of data filtering, discovery of outliers, classification, clustering, and association rule mining and time series. Programs used: R, Weka, Qctave and others.
Optimization and creation of analytical algorithms in HPC environment of business process data visualization and analysis. Visual analysis of generated data for business processes applying common visualization methodologies of data analysis and processes in HPC environment. Structural, visual and descriptive analysis considering data multidimensionality and complexity of the process in applied business process environment. Programs used R,Weka, Octave, Gaussian, Gamess and others.
Creation of massive data management and analysis algorithms using cloud computing. Creation, experimental usage and evaluation of “Big data” or even massive data databases in HPC and cloud computing environments. Programs used: NoSQL, Hadoop, BigTable and others.
Development of management and analytical algorithms of sensors and stream data in HPC and cloud computing. Implementation of algorithms of constantly evolving and regularly updated data models and similarity of time series. Application of essential temporal properties in research and algorithms for sensorial and geographic data. Programs used PostgreSQL, TPR indexes, streaming DB and others.
Relocation and data analysis of business processes in cloud computing. Customization and experimental evaluation of Business Systems for transition to cloud computing environments. Consulting and installation of commercial or open-source cloud computing environment. Programs used: S3, OpenNebula, OpenStack, VMware (ESXi), Hyper-V, XenServer, KVM, OpenVZ, VirtualBox and others.
Calculations and creation of algorithms for video and audio processing. Extraction of properties for conventional (photo and video) and medical images. The development of efficient algorithms for content image search and massive processing. Programs used: FFTW, WT, POV-Ray, and others.
Expert consulting in IT area. Expert consulting on IT product properties, non-trivial solutions and their evaluation. Analysis and application of new research methods involving VU MIF researchers.
Expert consulting and training strategies in Cyber Security area. Analysis of Cyber Security issues in business process and threat assessment. Tabletop and cyber range environments involving VU MIF researchers.
More information about the supercomputer resources and opportunities find here.
1. Fill in the ordering form
All customers must fill in an ordering form* and read general conditions for using IT Research center services.
- General conditions for using IT research center services
- Ordering form
- Users' list (must be included if there will be more than 3 users per one ordering form)
* Students must provide a form signed by his/her lecturer.
2. Sign and deliver
We would be very grateful if the scientists and researchers, who have used our supercomputer resources for research or experimental purposes, would mention IT Research center in the acknowledgement of the articles that will be published in scientific and popular science journals. For your convenience we offer a couple of examples:
- “The authors are thankful for the high performance computing resources provided by the Information Technology Research Center of Vilnius University.”
- “The authors are thankful for the HPC resources provided by the IT Research Center of Vilnius University.”
Definitions and interpretation
|Data||collectively all information that you submit to IT OAC via the Website. This definition incorporates, where applicable, the definitions provided in General Data Protection Regulation (GDPR);|
|Cookies||a small text file placed on your computer by this Website when you visit certain parts of the Website and/or when you use certain features of the Website. Details of the cookies used by this Website are set out in the clause below (Cookies);|
we or us
|VU MIF IT OAC Naugarduko str. 24, Vilnius, Lithuania;|
|UK and EU Cookie Law||the Privacy and Electronic Communications (EC Directive) Regulations 2003 as amended by the Privacy and Electronic Communications (EC Directive) (Amendment) Regulations 2011;|
|User or you||any third party that accesses the Website and is not either (i) employed by IT OAC and acting in the course of their employment or (ii) engaged as a consultant or otherwise providing services to IT OAC and accessing the Website in connection with the provision of such services;|
|Website||the website that you are currently using, https://hpc.mif.vu.lt, and any sub-domains of this site unless expressly excluded by their own terms and conditions.|
- the singular includes the plural and vice versa;
- a reference to a person includes firms, companies, government entities, trusts and partnerships;
- "including" is understood to mean "including without limitation";
- reference to any statutory provision includes any modification or amendment of it;
We may collect the following Data, which includes personal Data, from you or your Home Organisation via eduGAIN:
2. Job Title;
3. Contact Information such as email addresses and telephone numbers;
4. IP address (automatically collected);
5. Web browser type and version (automatically collected);
6. Operating system (automatically collected);
Our use of Data
1. For purposes of the GDPR, IT OAC is the "data controller".
2. We will retain any Data you submit for 12 months from the account termination.
3. Unless we are obliged or permitted by law to do so, and subject to any third party disclosures specifically set out in this policy, your Data will not be disclosed to third parties. This includes our affiliates and / or other companies within our group.
4. All personal Data is stored securely in accordance with the principles of the GDPR. For more details on security see the clause below (Security).
5. Any or all of the above Data may be required by us from time to time in order to provide you with the best possible service and experience when using our Website. Specifically, Data may be used by us for the following reasons:
1. internal record keeping;
2. improvement of our products / services;
Third party websites and services
1. IT OAC may, from time to time, employ the services of other parties for dealing with certain processes necessary for the operation of the Website. The providers of such services have access to certain personal Data provided by Users of this Website.
Links to other websites
Changes of business ownership and control
2. In the above instances, we will take steps with the aim of ensuring your privacy is protected.
Controlling use of your Data
Wherever you are required to submit Data, you will be given options to restrict our use of that Data. This may include the following:
1. use of Data for direct marketing purposes; and
2. sharing Data with third parties.
Functionality of the Website
1. To use all features and functions available on the Website, you may be required to submit certain Data.
1. You have the right to ask for a copy of any of your personal Data held by IT OAC (where such Data is held). The first copy is free of charge, following copies may incur a small fee, which will not exceed 10 EUR.
2. If you find out that the way we are processing data is against the law, you have the right to submit a claim to Vilnius University data protection officer.
1. Data security is of great importance to IT OAC and to protect your Data we have put in place suitable physical, electronic and managerial procedures to safeguard and secure Data collected via this Website.
2. If password access is required for certain parts of the Website, you are responsible for keeping this password confidential.
3. We endeavour to do our best to protect your personal Data. However, transmission of information over the internet is not entirely secure and is done at your own risk. We cannot ensure the security of your Data transmitted to the Website.
2. All Cookies used by this Website are used in accordance with current UK and EU Cookie Law.
3. Before the Website places Cookies on your computer, you will be presented with a message bar requesting your consent to set those Cookies. By giving your consent to the placing of Cookies, you are enabling IT OAC to provide a better experience and service to you. You may, if you wish, deny consent to the placing of Cookies; however certain features of the Website may not function fully or as intended.
4. This Website may place the following Cookies:
|Type of Cookie||Purpose|
|Strictly necessary cookies||These are cookies that are required for the operation of our website. They include, for example, cookies that enable you to log into secure areas of our website, use a shopping cart or make use of e-billing services.|
|Analytical/performance cookies||They allow us to recognise and count the number of visitors and to see how visitors move around our website when they are using it. This helps us to improve the way our website works, for example, by ensuring that users are finding what they are looking for easily.|
|Functionality cookies||These are used to recognise you when you return to our website. This enables us to personalise our content for you, greet you by name and remember your preferences (for example, your choice of language or region).|
5. You can choose to enable or disable Cookies in your internet browser. By default, most internet browsers accept Cookies but this can be changed. For further details, please consult the help menu in your internet browser.
6. You can choose to delete Cookies at any time; however you may lose any information that enables you to access the Website more quickly and efficiently including, but not limited to, personalisation settings.
7. It is recommended that you ensure that your internet browser is up-to-date and that you consult the help and guidance provided by the developer of your internet browser if you are unsure about adjusting your privacy settings.
3. Unless otherwise agreed, no delay, act or omission by a party in exercising any right or remedy will be deemed a waiver of that, or any other, right or remedy.
4. This Agreement will be governed by and interpreted according to the law of Lithuania. All disputes arising under the Agreement will be subject to the exclusive jurisdiction of the Lithuanian courts.
Data Protection Code of Conduct
Your personal data will be protected according to the Code of Conduct for Service Providers, a common standard for the research and higher education sector to protect your privacy.
You may contact IT OAC by email at .
03 November 2020
1. Who can use IT OAC infrastructure?
IT OAC main aim is to serve Vilnius University academic society.
We also provide services for private organisations - for that, please contact us on to agree on the size and billing details of your job.
2. How to use IT OAC infrastructure?
To gain access you have register yourself by creating an account in IT OAC portal.
For private organisations or other university representatives who cannot identify themselves with VU SSO authentication system, the accounts are created by IT OAC staff.
3. When can I start using?
Access to the resources is granted through the queue system to balance the load and access between different users.
In order to get your job in the queue, it has to be created and queued by the rules specified in the user guides.
User groups might also be assigned a priority mark which can also change the order of the queue.
4. Service providers’ rights and responsibilities
- Service providers provide users with user guides (published on the website) and additional guidance (by email, phone, in person) when needed.
- Service providers give their best to help users with user’s specific software, but cannot give any guarantees.
- Service is provided as best effort and service providers are not held responsible for any data loss, leakage or damage caused by force majeure, the user activity or inactivity or a third party whose access has become possible due to (in)activity of the user.
5. Users’ rights and responsibilities
- By default users are allowed to use IT OAC infrastructure solely for research and studies. IT OAC resources can be used for other legal activities only on previous written agreement.
- Users must use IT OAC resources in a way that doesn’t cause unnecessary waste of resources or other users work or time.
- Users must keep their login data in private. Accessing resources with someone elses login credential is strictly forbidden.
- In case of any possible security threats (e.g leakage of login credentials), user must contact IT OAC staff immediately and also give his/her best to avoid potential damage to the infrastructure.
You will find the answer to the question “Why do you need a supercomputer?” by reading the reviews of Vilnius University Faculty of Mathematics and Informatics staff, students and business partners. The team of the faculty is happy to be able to overcome the accumulated experience in solving important scientific, study and business tasks that require the use of efficient computing resources. From professor to student, from business representatives to individuals, these are the supercomputer users of the Faculty of Mathematics and Informatics who thank the faculty team for their professional advice and computational resources, and we thank them for sharing their results.
Acknowledgments from scientists
Early detection of COVID-19 is of vital importance. The group of scientists’ study is aimed to automatically detect COVID-19 disease from CXR (chest radiography imaging) images while maximizing the accuracy in detection. Their proposed framework involves image enhancement technique using dataset which consists of three classes: COVID-19, viral pneumonia and normal CXR imagery. To establish the robustness of the proposed model, stratified 5-fold cross-validation is carried out. The results suggest that image enhancement, segmentation and future fusion methods used in this study could indeed improve classification results. The scientists are thankful for the high-performance computing resources provided by the Information Technology Open Access Center at the Faculty of Mathematics and Informatics of Vilnius University Information Technology Research Center. Read article.
The scientists of Vilnius University
Rising numbers and sophistication of security threats in the digital domain cause an increase in the demand for skilled cybersecurity professionals. In response, cybersecurity exercises, and in particular—cyber defence exercises (CDX) are becoming ever more popular. The goal of our research is to provide a proper methodology to optimise the exercises so that every team and each participant, including a non-technical trainee, are adequately evaluated and trained using the allocated resources most effectively. The authors are thankful for the high-performance computing resources provided by the Information Technology Open Access Center at the Faculty of Mathematics and Informatics of Vilnius University Information Technology Research Center. Read article.
The scientists of Cyber Security Lab
The group of scientists researched forecasting methods and modeling techniques which are important tools for the situations caused by COVID-19 virus. The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions. The paper proposes data recording and machine-learning-based analysis using data to validate country forecasts in order to predict COVID-19 proliferation trends and assess risk. The authors are thankful for the high-performance computing resources provided by the Information Technology Open Access Center at the Faculty of Mathematics and Informatics of Vilnius University Information Technology Research Center. Read article.
The scientists of
Institute of Data Science and Digital Technologies and
Institute of Applied Mathematics
Defended dissertation "Development of Tumor Microenvironment-Oriented Digital Pathology Methods for Whole Slide Image Segmentation and Classification" author is thankful for the high-performance computing resources provided by the Information Technology Open Access Center at the Faculty of Mathematics and Informatics of Vilnius University Information Technology Research Center.
Dr. Mindaugas Morkūnas
Increasing intensity in maritime traffic pushes the requirement in better prevention-oriented incident management system. The scientists research results depict that both the autoencoder-based and wild bootstrapping region prediction algorithms can predict vessel trajectory and be applied for abnormal marine traffic detection by evaluating obtained prediction region in an unsupervised manner with desired prediction probability. Information about the research can be found in this article https://www.journals.vu.lt/nonlinear-analysis/article/view/23056/23620. Researchers thankful for the Information Technology Open Access Center at the Faculty of Mathematics and Informatics of Vilnius University for the supercomputer resources provided during this research.
The scientists of
Institute of Data Science and Digital Technologies and
Institute of Applied Mathematics
Defended dissertation "Semi-supervised and Unsupervised Machine Learning Methods for Sea Traffic Anomaly Detection" author is thankful for the high-performance computing resources provided by the Information Technology Open Access Center at the Faculty of Mathematics and Informatics of Vilnius University Information Technology Research Center.
Dr. Julius Venskus
"In this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation only. The assumption is that the speech audio signal carries sufficient emotional information to detect and retrieve it. Several two-dimensional acoustic feature spaces, such as cochleagrams, spectrograms, mel-cepstrograms, and fractal dimension-based space, are employed as the representations of speech emotional features. A convolutional neural network (CNN) is used as a classifier. The results show the superiority of cochleagrams over other feature spaces utilized. In the CNN-based speaker-independent cross-linguistic speech emotion recognition (SER) experiment, the accuracy of over 90% is achieved, which is close to the monolingual case of SER. Read article "
Institute of Data Science and Digital Technologies
Image and Signal Analysis Group
Feedback and thanks from doctoral students
“We used the VU MIF supercomputer for large-scale computations to model chemical processes in electrochemical microscopy. The results have been published in high-level application journals. "
“MIF supercomputer resources are useful in interdisciplinary research with scientists at the VU GMC Institute of Biochemistry. The subject of these investigations is the electrochemical properties of damaged (defective) phospholipid membranes. The supercomputer analyzes a large number of three-dimensional models of these membranes using the finite element method (FEM). This simulation avoids the complexity of working with real membranes in the laboratory and allows you to obtain the required information on the properties of the membranes being studied more quickly."
“At VU MIF Supercomputer, we are conducting research on algorithms for electroencephalogram (EEG) analysis. A supercomputer is especially useful for such research because we can test many algorithm configurations at a time and further explore the best one. Other algorithms we can parallelize, then we get acceleration on the supercomputer. We are currently investigating algorithms for EEG peak search and classification based on diagnosis, and apply the results to writing a doctoral dissertation, preparing scientific publications, and giving presentations at international and national scientific conferences. ”
A.V. Misiukas Misiūnas
Acknowledgments from the final theses
The graduate of the VU Faculty of Medicine is thankful for the provided IT resources by the ITAPC team. She managed to defend her master's thesis on the topic "Investigation of eye fundus image quality on vascular segmentation using deep neural networks" successfully.
Successfully defended bachelor thesis "An investigation of semi-supervised training methods for facial feature prediction" had been written by the author, who has graduated the "Information Systems Engineering" bachelor's studies. He is grateful for the opportunity to use ITAPC supercomputer for study purposes. The aim of the thesis research was to analyse and create semi-supervised learning method which would produce valuable information about unlabelled data and help during the training phase.
The graduate, who has successfully completed the VU MIF bachelor's study program "Econometrics" and defended her bachelor's thesis on the topic "Assessing the popularity of youtube videos using publicly available metadata", thanks the Information Technology Open Access Research Center for resources. This paper analyses the video metadata and derived parameters collected by the YouTube Data Application Programming Interface. After assessing significant differences in means among popularity groups by using statistical tests, data clustering algorithms: k-means and self-organising neural networks were applied, to search for trends in the formation of popularity groups. Classification of video popularity was also performed using three machine learning methods: support vector machine, random forest and multinomial logistic regression classifiers. A comparative analysis of the algorithms was carried out and the feature sets that most accurately classify the popularity level were selected. The aim of the final work was to contribute to the development of exception identification algorithms that are able to efficiently process traffic data.
The graduate, who has successfully completed the VU MIF master's study program "Modelling and Data Analysis" and defended his master's thesis on the topic "Outlier detection in multidimensional streaming data", thanks the Information Technology Open Access Research Center. The aim of the final work was to contribute to the development of exception identification algorithms that are able to efficiently process traffic data. VU MIF IT OARC supercomputer resources were used for the research of the master's thesis.
Business and other reviews
At the Faculty of Mathematics and Informatics of Vilnius University, with the help of HPC resources, Novian Technologies performed the design of another supercomputer for solving the problems of hydrometeorology in one of the 10 largest countries in the world. Based on the computational tasks provided by the customer, Novian Technologies has designed an individual HPC infrastructure (computing nodes, storage, network bandwidth, etc.) capable of solving specific hydrometeorological / climate change challenges in a given time. We are pleased to be able to present the customer with highly accurate results from calculations performed in a real-world HPC environment and using real-world computing power rather than assumptions. Accurate calculation results allowed the customer to safely plan the required capacity of equipment without a large margin, and thus save money.
Ltd. Novian Technologies
“The IT Research center team is characterized by promptness and goodwill. Effective communication allows for productive time planning, which is especially important during events, and goodwill collaboration ensures the quality of our organization's goals. ”
PI "Turing School"
"It's easy to work with the IT Research center team. There are rules in mature business where a verbal agreement equates to a written commitment. This way of communicating allows results to be achieved very quickly without bursting into the bureaucratic jungle."