High Performance Linpack ( HPL) is an industry standard benchmark used in measuring the computational power of High Performance Clusters. In contrary to HPC clusters consisting of equal computational nodes, running HPL on heterogeneous HPC clusters, built up of a computing nodes with different computational power, showed in most cases poor efficiency. In such type of clusters, efficiency of HPL further decreases if the speed of interconnect links between computing nodes is different. In order to improve HPL efficiency on such a clusters, one needs to optimally balance HPL workload on computing nodes accordingly to their computational power, and at the same time, take into the consideration the speed of communication links between them. Our thesis is that the problem of efficiently running HPL on heterogeneous HPC cluster is solvable, and that one can formulate it as a Semidefinite Optimization of Second Eigenvalue in Magnitude (SLEM) matrix describing data-flow of HPL in a cluster. In order to test a validity of such an approach, we run a series of HPL benchmarks on Isabella HPC cluster, both optimized respective to SLEM and non-optimized. By comparing results obtained with SLEM optimization of HPL against non-optimized HPL, we were able to identify a huge improvement in HPL efficiency when using SLEM. Moreover, by taking into the consideration memory sizes of computational nodes, we were able to improve SLEM optimization of HPL further.

In recent years performance of High Performance Computing Clusters took precedence over their power consumption. However, costs of energy and demand for ecologically acceptable IT solutions are higher than ever before, therefore a need for HPC clusters with acceptable power consumption becomes increasingly important. Consequently, the Green500 list, which takes into account both performance and power consumption of HPC clusters, almost reached the popularity of the Top500 list. Interestingly, the Green500 list is not an opponent to Top500 list; its core idea is to complement the Top500. Therefore, the Top500 list still serves as the basis for the Green500 list, and its numbers regarding measured HPL performance, are a basis for calculating the Green500 list. Indeed, the Green500 is the Top500 list ordered by HPL measured performance per Watt. Rmax numbers gained from High Performance Linpack benchmarks serve as performance input parameters, and total power consumed during execution of HPL on a certain HPC clusters is a power consumption parameter. The critical question remains: how to measure the consumed power correctly? This paper proposes that if it is not possible to measure the consumed power, one can still use maximum power consumption numbers rated from hardware vendors to find at least the lower bound green efficiency of HPC clusters. The main idea behind this approach is that Rmax values found on Top500 list never achieve Rpeak theoretical values, and that even most efficient HPL benchmark can never utilize computing nodes at their maximum. Furthermore by comparing MFLOPS/W results we gained with those found on Green500 list, we noted the excellent efficiency of the new HPC Isabella cluster recently powered on at University Computing Centre in Zagreb, ranking in just behind University of North Carolina KillDevil Top500 super cluster.

Modern advances in technology allow new telemonitoring systems for prevention, early diagnosis and management of chronic and degenerative conditions. These remote monitoring systems reduce the need for recurring visits to the hospital, allow physicians better insight into the patient's state and help determine the necessary level of care for each individual patient. Telemonitoring can also be applied on a long-term basis to elderly persons to detect gradual deterioration in their health status, which may imply a reduction in their ability to live independently. The functional potential of the upper extremities is a good indicator of how well a person can live independently and can also help to determine their health status. This article presents an OSGi residential gateway based telemonitoring system and a case study of its application in health telemonitoring, especially considering locomotion status of the upper extremities. In this case study, two electronic devices, used for monitoring the functional degradation of upper extremities, are introduced into the presented system. One of those two devices records dynamic properties of the hand grip (e.g. grip speed, grip stability, grip endurance) and the other device records hand movement dynamic properties (e.g. speed of movement, spectral components).

Infrared (IR) thermography determines the surface temperature of an object or human body using thermal IR measurement camera. It is an imaging technology which is con tactless and completely non-invasive. These properties make IR thermography a useful method of analysis that is used in various industrial applications to detect, monitor and predict irregularities in many fields from engineering to medical and biological observations. This paper presents a conceptual model of Medical 3D Thermography which introduces standardised 3D thermogram creation, representation and analysis concepts useful for variety of medical applications. The creation of 3D thermograms is possible through combining 3D scanning methods with thermal imaging. We describe development of a 3D thermography system integrating passive thermal imaging with 3D geometrical data from active 3D scanner:We outline the potential benefits of this system in medical applications. In particular we emphasize the benefits of using this system for preventive detection of breast cancer

Major amount of thermal radiation emitted by objects is located in a small part of the infrared spectrum of electromagnetic radiation, called the thermal infrared spectrum, and can be observed and measured using thermal infrared measurement cameras. Measuring heat transfer by radiation has proven to be very valuable in medicine. One such medical application is the early detection and monitoring of breast cancers. Since tumors cause the rise in local tissue temperature, they can be observed as small embedded heat sources. The focus of this paper is the construction of new artificial test sets for heat source parameter estimation (such as the source depth, volume and intensity/size), to be used before clinical trials. A mixture of ballistic gelatin was used as a heat conductance medium, while a resistor grid (consisting of nine resistors) was used as a heat source, embedded inside the gelatin. Simulation procedure was conducted, resulting in a rank list of parameter configurations for every heat source of the grid. The expected values of parameters were found to be high on the configuration list, with about the first 20% of configurations present in the search space. This paper shows a convenient and effective way of testing parameter estimation methods. On the other hand, although ballistic gelatin presents a homogeneous mixture for heat transfer, with similar density and elastic properties as the living tissue, it does not necessarily have the same thermal conductance. Therfore the possibilities for future development of new materials for comparing parameter estimation methods on artificial test sets should be considered, as well as development of more complex materials consisting of multiple layers and thus more accurately emulating the heat dispersion in human bodies.

All objects emit infrared radiation at differing levels, depending on their temperature. Infrared thermal imaging is the technique of producing an image from infrared radiation. This thermal image represents two-dimensional distribution of the infrared radiation emitted by object displaying the object's temperatures. High performance computing data centres deploy high-density blade servers that have high power and cooling requirements. Thermal management techniques are needed in different levels to ensure data centre's reliability and economical operating cost. Appropriately designed and accurate temperature monitoring is essential for every thermal management techniques. Infrared thermal imaging can provide a fine-resolution thermal image of blade systems deployed in data canter. This paper outlines an application of infrared thermal imaging in blade based data centres. For this purpose thermal monitoring of computer cluster at the blade-level is conducted using infrared thermal imaging monitoring system at the blade enclosure-level.

Infrared (IR) thermography determines the surface temperature of an object or human body using IR camera. It is an imaging technology which is contactless and completely non-invasive. These properties make infrared thermography a useful method of analysis that is used in various industrial applications to detect, monitor and predict irregularities in many fields from engineering to medical and biological observations. This paper presents 3D thermography based on the combination of active visual 3D imaging technology and passive thermal imaging technology. We describe development of a 3D thermography system integrating thermal imaging with 3D geometrical data from active 3D scanner. We also outline the potential benefits of this system in medical applications. In particular, we emphasize the benefits of using this system for detection of breast cancer.

The dissipation of thermal radiation can be observed using thermal infrared cameras which generate images based on the amount of input radiation belonging to a small part of the electromagnetic spectrum (with wavelengths from 7 µm to 15 µm). Since thermal imaging is a simple, contactless, non-invasive and inexpensive imaging method, it is widely applicable in industry, medicine and research. The most common type of thermal imaging involves taking and analyzing only a single thermal image, and it is thus called static thermal imaging. In cases when a thermal process cannot be approximated as static, dynamic thermal imaging and analysis are applied. The idea of combining thermal imaging with 3D scanning methods has spawned in the last few years. 3D thermal imaging can have many applications and purposes, ranging from thermogram rectification to the creation of standardized 3D thermal models of various subjects that can later be used for comparison and evaluation. Although 3D thermal imaging systems exist, all of the examined ones were targeted on the acquisition and analysis of static 3D thermal models. This paper presents the development of a 4D thermography system through integration of dynamic 3D scanning and thermographic imaging, additionally providing markerless motion analysis, which together enable practical, non-invasive, accurate and automatic monitoring of the temperature changes in the human body, and the characterization of human motion. The workflow of the designed concept is outlined, and the components of the constructed system are thoroughly explained. The process of calibration of the system is described, as well as the methods of motion detection and analysis. Great emphasis is given on the possible medical applications of a 4D thermography system, such as medical diagnostics, human locomotive system rehabilitation and health status monitoring over prolonged time periods.

Thermal imaging is a non-invasive, non-contact functional imaging method used in temperature measurements. It provides an insight to metabolic and other processes within human body. In this paper a general simulation model that can be used to estimate the depth and size of the heat source embedded underneath the surface of an object is presented. Simulations are performed on two sets of input data, acquired with a 3D thermography system, consisting of a 3D scanner and a thermal camera. The procedure is based on describing the heat source radiation using a function (in this paper Gaussian function was used), and searching the parameter space. For every parameter configuration, the color of each vertex of the scanned 3D model is changed according to the defined function. The model is rendered and the image compared to the one taken with a thermal camera. Results of this process are presented in the form of a sorted list, with the most likely configuration at the first place. Method described in this paper can have a wide spread of possible applications in technology and engineering as well as medicine. For example, if it can be assumed that a tumour can be approximated by a point source, this procedure can then also be applicable in analysis of breast or other types of tumours.

The foundation of successful software product development today is establishing an effective and efficient teamwork. In order to manage large software development projects it is needed to manage and coordinate virtual teams of programmers, engineers, business analysts and other project stakeholders. Trust is required for effective team communication. Presented software tool enhances cooperative work support by improving virtual team communication. Implemented software architecture is modular and easily upgradeable, offering multithreaded client-server communication with multiple servers. Secure communication eminent for maintaining message integrity and confidentiality among team members is implemented using SSL protocol on connections between all servers and clients.