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Katalog Publikacji
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An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments
PublikacjaThe new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main...
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Blockchain technologies to address smart city and society challenges
PublikacjaNew Information and Communications Technologies (ICT) are changing the way in which the world works. These technologies provide new tools to face the issues of contemporary society (poverty, migrations, sustainable development challenges, governance, etc.). Among them, blockchain emerge as a disruptive technology able to make things in a completely different and innovative way. They can provide solutions where before there were...
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Detection of the Bee Queen Presence Using Sound Analysis
PublikacjaThis work describes the system and methods of data analysis we use for beehive monitoring. We present overview of the hardware infrastructures used in hive monitoring systems and we describe algorithms used for analysis of this kind of data. Based on acquisited signals we construct the application that is capable to detect an absence of honey bee queen. We describe our method of signal analysis and present results that allow us...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublikacjaTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments
PublikacjaThe paper presents state of the art of energy-aware high-performance computing (HPC), in particular identification and classification of approaches by system and device types, optimization metrics, and energy/power control methods. System types include single device, clusters, grids, and clouds while considered device types include CPUs, GPUs, multiprocessor, and hybrid systems. Optimization goals include various combinations of...
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Comparative Analysis of Text Representation Methods Using Classification
PublikacjaIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Future research directions in design of reliable communication systems
PublikacjaIn this position paper on reliable networks, we discuss new trends in the design of reliable communication systems. We focus on a wide range of research directions including protection against software failures as well as failures of communication systems equipment. In particular, we outline future research trends in software failure mitigation, reliability of wireless communications, robust optimization and network design, multilevel...
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MERPSYS: An environment for simulation of parallel application execution on large scale HPC systems
PublikacjaIn this paper we present a new environment called MERPSYS that allows simulation of parallel application execution time on cluster-based systems. The environment offers a modeling application using the Java language extended with methods representing message passing type communication routines. It also offers a graphical interface for building a system model that incorporates various hardware components such as CPUs, GPUs, interconnects...
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Performance evaluation of Unified Memory with prefetching and oversubscription for selected parallel CUDA applications on NVIDIA Pascal and Volta GPUs
PublikacjaThe paper presents assessment of Unified Memory performance with data prefetching and memory oversubscription. Several versions of code are used with: standard memory management, standard Unified Memory and optimized Unified Memory with programmer-assisted data prefetching. Evaluation of execution times is provided for four applications: Sobel and image rotation filters, stream image processing and computational fluid dynamic simulation,...
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Modelling the malware propagation in mobile computer devices
PublikacjaNowadays malware is a major threat to the security of cyber activities. The rapid develop- ment of the Internet and the progressive implementation of the Internet of Things (IoT) increase the security needs of networks. This research presents a theoretical model of malware propagation for mobile computer devices. It is based on the susceptible-exposed- infected-recovered-susceptible (SEIRS) epidemic model. The scheme is based on...
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Distributed Architectures for Intensive Urban Computing: A Case Study on Smart Lighting for Sustainable Cities
PublikacjaNew information and communication technologies have contributed to the development of the smart city concept. On a physical level, this paradigm is characterised by deploying a substantial number of different devices that can sense their surroundings and generate a large amount of data. The most typical case is image and video acquisition sensors. Recently, these types of sensors are found in abundance in urban spaces and are responsible...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublikacjaBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublikacjaThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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RDF dataset profiling - a survey of features, methods, vocabularies and applications
PublikacjaThe Web of Data, and in particular Linked Data, has seen tremendous growth over the past years. However, reuse and take-up of these rich data sources is often limited and focused on a few well-known and established RDF datasets. This can be partially attributed to the lack of reliable and up-to-date information about the characteristics of available datasets. While RDF datasets vary heavily with respect to the features related...
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A method for counting people attending large public events
PublikacjaThe algorithm for people counting in crowded scenes, based on the idea of virtual gate which uses optical flow method is presented. The concept and practical application of the developed algorithm under real conditions is depicted. The aim of the work is to estimate the number of people passing through entrances of a large sport hall. The most challenging problem was the unpredicted behavior of people while entering the building....
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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublikacjaIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...
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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublikacjaA concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...
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Survey of Methodologies, Approaches, and Challenges in Parallel Programming Using High-Performance Computing Systems
PublikacjaThis paper provides a review of contemporary methodologies and APIs for parallel programming, with representative technologies selected in terms of target system type (shared memory, distributed, and hybrid), communication patterns (one-sided and two-sided), and programming abstraction level. We analyze representatives in terms of many aspects including programming model, languages, supported platforms, license, optimization goals,...
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Performance evaluation of unified memory and dynamic parallelism for selected parallel CUDA applications
PublikacjaThe aim of this paper is to evaluate performance of new CUDA mechanisms—unified memory and dynamic parallelism for real parallel applications compared to standard CUDA API versions. In order to gain insight into performance of these mechanisms, we decided to implement three applications with control and data flow typical of SPMD, geometric SPMD and divide-and-conquer schemes, which were then used for tests and experiments. Specifically,...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Optimization of Execution Time under Power Consumption Constraints in a Heterogeneous Parallel System with GPUs and CPUs
PublikacjaThe paper proposes an approach for parallelization of computations across a collection of clusters with heterogeneous nodes with both GPUs and CPUs. The proposed system partitions input data into chunks and assigns to par- ticular devices for processing using OpenCL kernels defined by the user. The sys- tem is able to minimize the execution time of the application while maintaining the power consumption of the utilized GPUs and...
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Buzz-based recognition of the honeybee colony circadian rhythm
PublikacjaHoneybees are one of the highly valued pollinators. Their work as individuals is appreciated for crops pollination and honey production. It is believed that work of an entire bee colony is intense and almost continuous. The goal of the work presented in this paper is identification of bees circadian rhythm with a use of sound-based analysis. In our research as a source of information on bee colony we use their buzz that have been...
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Multi-agent large-scale parallel crowd simulation
PublikacjaThis paper presents design, implementation and performance results of a new modular, parallel, agent-based and large scale crowd simulation environment. A parallel application, implemented with C and MPI, was implemented and run in this parallel environment for simulation and visualization of an evacuation scenario at Gdansk University of Technology, Poland and further in the area of districts of Gdansk. The application uses a...
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Analyzing energy/performance trade-offs with power capping for parallel applications on modern multi and many core processors
PublikacjaIn the paper we present extensive results from analyzing energy/performance trade-offs with power capping observed on four different modern CPUs, for three different parallel applications such as 2D heat distribution, numerical integration and Fast Fourier Transform. The CPU tested represent both multi-core type CPUs such as Intel⃝R Xeon⃝R E5, desktop and mobile i7 as well as many-core Intel⃝R Xeon PhiTM x200 but also server, desktop...
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External Validation Measures for Nested Clustering of Text Documents
PublikacjaAbstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to...
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Mining relations between wikipedia categories
PublikacjaOpisano metody indukcji powiązań pomiędzy kategoriami organizującymi zbiór dokumentów. Przedstawiono wyniki zastosowania proponowanego podejścia dla poprawy systemu kategorii Wikipedii.
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Words context analysis for improvement of information retrieval
PublikacjaIn the article we present an approach to improvement of retrieval informationfrom large text collections using words context vectors. The vectorshave been created analyzing English Wikipedia with Hyperspace Analogue to Language model of words similarity. For test phrases we evaluate retrieval with direct user queries as well as retrieval with context vectors of these queries. The results indicate that the proposed method can not...
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Thresholding Strategies for Large Scale Multi-Label Text Classifier
PublikacjaThis article presents an overview of thresholding methods for labeling objects given a list of candidate classes’ scores. These methods are essential to multi-label classification tasks, especially when there are a lot of classes which are organized in a hierarchy. Presented techniques are evaluated using the state-of-the-art dedicated classifier on medium scale text corpora extracted from Wikipedia. Obtained results show that the...
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Remote task submission and publishing in BeesyCluster: security and efficiency of Web Service interface
PublikacjaPrezentujemy nowy system BeesyCluster, który stanowi łatwy w użyciu portal dostępowy do rozszerzalnej sieci usług wdrożonych i opublikowanych na klastrach/komputerach PC z wirtualnymi płatnościami za wykorzystanie usług. Administratorzy/użytkownicy mogą dołączać klastry/komputery PC dostępne poprzez SSH kliknięciem myszy bez konieczności dalszej konfiguracji na klastrze/komputerze PC udostępniającego. Ponadto, użytkownicy mogą...
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Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms
PublikacjaOver the past few decades, the increasing number of vehicles and imperfect road traffic management have been sources of congestion in cities and reasons for deteriorating health of its inhabitants. With the help of computer simulations, transport engineers optimise and improve the capacity of city streets. However, with an enormous number of possible simulation types, it is difficult to grasp valuable, innovative solutions which...
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Parallelization of large vector similarity computations in a hybrid CPU+GPU environment
PublikacjaThe paper presents design, implementation and tuning of a hybrid parallel OpenMP+CUDA code for computation of similarity between pairs of a large number of multidimensional vectors. The problem has a wide range of applications, and consequently its optimization is of high importance, especially on currently widespread hybrid CPU+GPU systems targeted in the paper. The following are presented and tested for computation of all vector...
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Self–Organizing Map representation for clustering Wikipedia search results
PublikacjaThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
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Practical I-Voting on Stellar Blockchain
PublikacjaIn this paper, we propose a privacy-preserving i-voting system based on the public Stellar Blockchain network. We argue that the proposed system satisfies all requirements stated for a robust i-voting system including transparency, verifiability, and voter anonymity. The practical architecture of the system abstracts a voter from blockchain technology used underneath. To keep user privacy, we propose a privacy-first protocol that...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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KernelHive: a new workflow-based framework for multilevel high performance computing using clusters and workstations with CPUs and GPUs
PublikacjaThe paper presents a new open-source framework called KernelHive for multilevel parallelization of computations among various clusters, cluster nodes, and finally, among both CPUs and GPUs for a particular application. An application is modeled as an acyclic directed graph with a possibility to run nodes in parallel and automatic expansion of nodes (called node unrolling) depending on the number of computation units available....
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Simulation of parallel similarity measure computations for large data sets
PublikacjaThe paper presents our approach to implementation of similarity measure for big data analysis in a parallel environment. We describe the algorithm for parallelisation of the computations. We provide results from a real MPI application for computations of similarity measures as well as results achieved with our simulation software. The simulation environment allows us to model parallel systems of various sizes with various components...
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A model, design, and implementation of an efficient multithreaded workflow execution engine with data streaming, caching, and storage constraints
PublikacjaThe paper proposes a model, design, and implementation of an efficient multithreaded engine for execution of distributed service-based workflows with data streaming defined on a per task basis. The implementation takes into account capacity constraints of the servers on which services are installed and the workflow data footprint if needed. Furthermore, it also considers storage space of the workflow execution engine and its cost....
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Big Data Paradigm Developed in Volunteer Grid System with Genetic Programming Scheduler
PublikacjaArtificial intelligence techniques are capable to handle a large amount of information collected over the web. In this paper, big data paradigm has been studied in volunteer and grid system called Comcute that is optimized by a genetic programming scheduler. This scheduler can optimize load balancing and resource cost. Genetic programming optimizer has been applied for finding the Pareto solu-tions. Finally, some results from numerical...
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Semantic memory knowledge acquisition through active dialogues
PublikacjaSzereg zagadnień językowych nie może zostać rozwiązany bez pamięci semantycznej zawierającej opisy cech obiektów, Automatyczne tworzenie tego rodzaju pamięci jest wielkim wyzwaniem nawet dla prostych obszarów dziedzinowych. Implementacja pamięci semantycznej opartej na reprezentacji wiedzy poprzez powiązania obiektu z jego cechami pokazuje ciekawe zastosowania które nie zostały dotychczas zademonstrowane poprzez bardziej wyszukane...
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Benchmarking Performance of a Hybrid Intel Xeon/Xeon Phi System for Parallel Computation of Similarity Measures Between Large Vectors
PublikacjaThe paper deals with parallelization of computing similarity measures between large vectors. Such computations are important components within many applications and consequently are of high importance. Rather than focusing on optimization of the algorithm itself, assuming specific measures, the paper assumes a general scheme for finding similarity measures for all pairs of vectors and investigates optimizations for scalability...
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DEPTH IMAGES FILTERING IN DISTRIBUTED STREAMING
PublikacjaIn this paper we discuss the comparison of point cloud filters focusing on their applicability for streaming optimization. For the filtering stage within a stream pipeline processing we evaluate three filters: Voxel Grid, Pass Through and Statistical Outlier Removal. For the filters we perform series of the tests aiming at evaluation of changes of point cloud size and transmitting frequency (various fps ratio). We propose a distributed...
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Integration of compute-intensive tasks into scientific workflows in BeesyCluster
PublikacjaArtykuł prezentuje szczegóły projektowe i implementacyjne jak również symulacje naukowych scenariuszy z wymagającymi zadaniami na klastrach i komputerach PC. Autor wdrożył wsparcie dla scenariuszy naukowych do wcześniej opracowanego systemu BeesyCluster wdrożonego w Akademickim Centrum Komputerowym sieci TASK w Gdańsku na klastrze holk z 288 procesorami Itanium2. BeesyCluster pozwala użytkownikom na zarządzanie różnymi kontami...
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Depth Images Filtering In Distributed Streaming
PublikacjaIn this paper, we propose a distributed system for point cloud processing and transferring them via computer network regarding to effectiveness-related requirements. We discuss the comparison of point cloud filters focusing on their usage for streaming optimization. For the filtering step of the stream pipeline processing we evaluate four filters: Voxel Grid, Radial Outliner Remover, Statistical Outlier Removal and Pass Through....
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Checkpointing of Parallel MPI Applications using MPI One-sided API with Support for Byte-addressable Non-volatile RAM
PublikacjaThe increasing size of computational clusters results in an increasing probability of failures, which in turn requires application checkpointing in order to survive those failures. Traditional checkpointing requires data to be copied from application memory into persistent storage medium, which increases application execution time as it is usually done in a separate step. In this paper we propose to use emerging byte-addressable...
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Optimization of parallel implementation of UNRES package for coarse‐grained simulations to treat large proteins
PublikacjaWe report major algorithmic improvements of the UNRES package for physics-based coarse-grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time-consuming energy/force terms...
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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams
PublikacjaThe paper investigates parallel data processing in a hybrid CPU+GPU(s) system using multiple CUDA streams for overlapping communication and computations. This is crucial for efficient processing of data, in particular incoming data stream processing that would naturally be forwarded using multiple CUDA streams to GPUs. Performance is evaluated for various compute time to host-device communication time ratios, numbers of CUDA streams,...
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Teaching High Performance Computing Using BeesyCluster and Relevant Usage Statistics
PublikacjaThe paper presents motivations and experiences from using the BeesyCluster middleware for teaching high performance computing at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology. Features of BeesyCluster well suited for conducting courses are discussed including: easy-to-use WWW interface for application development and running hiding queuing systems, publishing applications as services...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublikacjaHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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Extended investigation of performance-energy trade-offs under power capping in HPC environments
Publikacja—In the paper we present investigation of performance-energy trade-offs under power capping using modern processors. The results are presented for systems targeted at both server and client markets and were collected from Intel Xeon E5 and Intel Xeon Phi server processors as well as from desktop and mobile Intel Core i7 processors. The results, when using power capping, show that we can find various interesting combinations of...