Dynamic Workload Parallelization and System Calibration on Single-Chip Cloud Computer

Many-core systems are emerging from the need of more computational power and power efficiency. However there are many issues which still revolve around the many-core systems. These systems need specialized software before they can be fully utilized and the hardware itself may differ from the conventional computational systems. To gain efficiency from many-core system, programs need to be parallelized. In many-core systems the cores are small and less powerful than cores used in traditional computing, so running a conventional program is not an efficient option. Also in Network-on-Chip based processors the network might get congested and the cores might work at different speeds. In this thesis is, a dynamic load balancing method is proposed and tested on Intel 48-core Single-Chip Cloud Computer by parallelizing a fault simulator. The maximum speedup is difficult to obtain due to severe bottlenecks in the system. In order to exploit all the available parallelism of the Single-Chip Cloud Computer, a runtime approach capable of dynamically balancing the load during the fault simulation process is used. The proposed dynamic fault simulation approach on the Single-Chip Cloud Computer shows up to 45X speedup compared to a serial fault simulation approach. Many-core systems can draw enormous amounts of power, and if this power is not controlled properly, the system might get damaged. One way to manage power is to set power budget for the system. But if this power is drawn by just few cores of the many, these few cores get extremely hot and might get damaged. Due to increase in power density multiple thermal sensors are deployed on the chip area to provide realtime temperature feedback for thermal management techniques. Thermal sensor accuracy is extremely prone to intra-die process variation and aging phenomena. These factors lead to a situation where thermal sensor values drift from the nominal values. This necessitates efficient calibration techniques to be applied before the sensor values are used. In addition, in modern many-core systems cores have support for dynamic voltage and frequency scaling. Thermal sensors located on cores are sensitive to the core's current voltage level, meaning that dedicated calibration is needed for each voltage level. In this thesis a general-purpose software-based auto-calibration approach is also proposed for thermal sensors to calibrate thermal sensors on different range of voltages.

THE ROLE OF DYNAMIC CAPABILITIES IN THE INTERNATIONALIZATION OF MEDIUM SIZED FINNISH MANUFACTURING FIRMS - A case for Sormat Oy

A rapidly changing business environment has necessitated most small and medium sized enterprises with international ambitions to reconsider their sources of competitive advantage. To survive in the face of a changing business environment, firms should utilize their dynamic organizational capabilities as well as their internationalization capabilities. Firms develop a competitive advantage if they can exploit their unique organizational competences in a new or foreign market and also if they can acquire new capabilities as a result of engaging in foreign markets. The acquired capabilities from foreign locations enhance the existing capability portfolio of a firm with a desire to internationalize. The study combined the research streams of SME organizational dynamic capability and internationalization capability to build a complete picture on the existing knowledge. An intensive case study was used for empirically testing the theoretical framework of the study and compared with the literature on various organizational capability factors and internationalization capabilities. Sormay Oy was selected because it is a successful medium sized company operating in Finland in the manufacturing industry which has a high international profile. In addition, it has sufficient rate of growth in sales that warrants it to engage internationally in matters such as, acquisitions, joint ventures and partnerships. The key findings of the study suggests that, medium sized manufacturing firms have a set of core competences arising from their organizational capabilities which were identified to be employee know how and relationship with stakeholders which aid the firm in its quest for attaining competitive advantage, ensuring production flexibility and gaining benefits present in a network. In addition, internationalization capabilities were identified under both the RAT test and CAT test whereby the primary findings suggests that, firms that outperform their competitors produce products that meet specific customer and country requirements, foresee the pitfalls of imitation brought about by the foreign local companies and members of a particular network through joint ventures, acquisitions or partnerships as well as those firms that are capable to acquire new capabilities in the foreign markets and successfully use these acquired capabilities to enhance or renew their capability portfolio for their competitive advantage. Additional significant findings under internationalization capabilities were discovered whereby, Sormay Oy was able to develop a new market space for its products despite the difficult institutional environment present in Russia.

A Belief rule-based environmental responsibility assessment system for small and medium-sized enterprises

Various environmental management systems, standards and tools are being created to assist companies to become more environmental friendly. However, not all the enterprises have adopted environmental policies in the same scale and range. Additionally, there is no existing guide to help them determine their level of environmental responsibility and subsequently, provide support to enable them to move forward towards environmental responsibility excellence. This research proposes the use of a Belief Rule-Based approach to assess an enterprise’s level commitment to environmental issues. The Environmental Responsibility BRB assessment system has been developed for this research. Participating companies will have to complete a structured questionnaire. An automated analysis of their responses (using the Belief Rule-Based approach) will determine their environmental responsibility level. This is followed by a recommendation on how to progress to the next level. The recommended best practices will help promote understanding, increase awareness, and make the organization greener. BRB systems consist of two parts: Knowledge Base and Inference Engine. The knowledge base in this research is constructed after an in-depth literature review, critical analyses of existing environmental performance assessment models and primarily guided by the EU Draft Background Report on "Best Environmental Management Practice in the Telecommunications and ICT Services Sector". The reasoning algorithm of a selected Drools JBoss BRB inference engine is forward chaining, where an inference starts iteratively searching for a pattern-match of the input and if-then clause. However, the forward chaining mechanism is not equipped with uncertainty handling. Therefore, a decision is made to deploy an evidential reasoning and forward chaining with a hybrid knowledge representation inference scheme to accommodate imprecision, ambiguity and fuzzy types of uncertainties. It is believed that such a system generates well balanced, sensible and Green ICT readiness adapted results, to help enterprises focus on making improvements on more sustainable business operations.