| 1. |
- Campeanu, Gabriel, 1982-
(författare)
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GPU-aware Component-based Development for Embedded Systems
- 2016
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Nowadays, more and more embedded systems are equipped with e.g., various sensors that produce large amount of data. One of the challenges of traditional (CPU-based) embedded systems is to process this considerable amount of data such that it produces the appropriate performance level demanded by embedded applications. A solution comes from the usage of a specialized processing unit such as Graphics Processing Unit (GPU). A GPU can process large amount of data thanks to its parallel processing architecture, delivering an im- proved performance outcome compared to CPU. A characteristic of the GPU is that it cannot work alone; the CPU must trigger all its activities. Today, taking advantage of the latest technology breakthrough, we can benefit of the GPU technology in the context of embedded systems by using heterogeneous CPU-GPU embedded systems.Component-based development has demonstrated to be a promising methology in handling software complexity. Through component models, which describe the component specification and their interaction, the methodology has been successfully used in embedded system domain. The existing component models, designed to handle CPU-based embedded systems, face challenges in developing embedded systems with GPU capabilities. For example, current so- lutions realize the communication between components with GPU capabilities via the RAM system. This introduces an undesired overhead that negatively affects the system performance.This Licentiate presents methods and techniques that address the component- based development of embedded systems with GPU capabilities. More concretely, we provide means for component models to explicitly address the GPU-aware component-based development by using specific artifacts. For example, the overhead introduced by the traditional way of communicating via RAM is reduced by inserting automatically generated adapters that facilitate a direct component communication over the GPU memory.Another contribution of the thesis is a component allocation method over the system hardware. The proposed solution offers alternative options in opti- mizing the total system performance and balancing various system properties (e.g., memory usage, GPU load). For the validation part of our proposed solutions, we use an underwater robot demonstrator equipped with GPU hardware.
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| 2. |
- Campeanu, Gabriel, 1982-
(författare)
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GPU Support for Component-based Development of Embedded Systems
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One pressing challenge of many modern embedded systems is to successfully deal with the considerable amount of data that originates from the interaction with the environment. A recent solution comes from the use of GPUs. Equipped with a parallel execution model, the GPU excels in parallel processing applications, providing an improved performance compared to the CPU.Another trend in the embedded systems domain is the use of component-based development. This software engineering paradigm that promotes construction of applications through the composition of software components, has been successfully used in the development of embedded systems. However, the existing approaches provide no specific support to develop embedded systems with GPUs. As a result, components with GPU capability need to encapsulate all the required GPU information in order to be successfully executed by the GPU. This leads to component specialization to specific platforms, hence drastically impeding component reusability.Our main goal is to facilitate component-based development of embedded systems with GPUs. We introduce the concept of flexible component which increases the flexibility to design embedded systems with GPUs, by allowing the system developer to decided where to place the component, i.e., either on the CPU or GPU. Furthermore, we provide means to automatically generate the required information for flexible components corresponding to their hardware placement, and to improve component communication. Through the introduced support, components with GPU capability are platform-independent, being capable to be executed on a large variety of hardware (i.e., platforms with different GPU characteristics). Furthermore, an optimization step is introduced, which groups connected flexible components into single entities that behave as regular components. Dealing with components that can be executed either by the CPU or GPU, we also introduce an allocation optimization method. The proposed solution, implemented using a mathematical solver, offers alternative options in optimizing particular system goals (e.g., memory and energy usage).
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| 3. |
- Feljan, Juraj, 1985-
(författare)
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Task Allocation Optimization for Multicore Embedded Systems
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Modern embedded systems are becoming increasingly performance intensive, since, on the one hand, they include more complex functionality than before, and one the other hand, the functionality that was typically realized with hardware is often moved to software. Multicore technology, previously successfully used for general-purpose systems, is penetrating into the domain of embedded systems. While it does increase the performance capacity, it also introduces the problem of how to allocate software tasks to the cores of the hardware platform, as different allocations exhibit different extra-functional properties. An intuitive example is allocating too many tasks to a core --- the core will be overloaded and tasks will miss their deadlines.This thesis addresses the issue of task allocation in multicore embedded systems. The overall goal of the thesis is to advance the way soft real-time multicore systems are developed, by providing new methods and tools that enable deciding already at design-time which task to run on which core, with respect to a number of timing-related extra-functional properties. To achieve this goal, we developed a model-based framework for task allocation optimization. The framework uses model simulation in order to obtain performance predictions for particular task allocations. This in turn enables testing a large number of allocation candidates in search for one that exhibits good timing-related performance. Apart from defining and implementing the framework, three additional contributions are provided, each tackling a particular aspect of the framework: the influence of task allocation on communication duration is studied and interpreted in the context of design-time model-based analysis; a novel heuristic for guiding task allocation optimization is defined; and finally, a novel optimization method combining performance prediction and performance measurement is defined.
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| 4. |
- Gaetana, Sapienza
(författare)
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Hardware/Software Partitioning Methodology for Embedded Applications using Multiple Criteria Decision Analysis
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The new hardware technologies enable execution of embedded systems applications on heterogeneous execution platforms. These platforms consist of different execution processing units, for example of CPUs, and FPGAs, that enable the application execution of software (SW) components, typically implemented as C/C++ code, and hardware (HW) components, implemented as VHDL code. This heterogeneity enables building dedicated components which can significantly improve the application performance. This, however, requires decisions on which components will be implemented as SW and which as HW execution units. This decision process in known as HW/SW partitioning, and is a subject of research of more than 20 years. Typical goals of this research was to find the optimal partitioning with respect to the system performance, and possibly a couple of other properties such as power consumption, or resource utilization (e.g. related to CPU memory footprint and FPGA area). However, by significant increase in complexity of the applications, and inclusion of different requirements, the partitioning decisions become more complex, as well as the entire development process with an integrated partitioning decision process. Today there is a lack of a systematic approach for partitioning complex applications. This thesis addresses this challenge. The main objective of the thesis is to design and build a systematic partitioning decision process that includes many requirements of different types. The thesis describes a new method MULTIPAR that includes the partitioning decision process for component-based embedded systems. The method is based on model-based engineering principles; components are analysed as models which can be implemented either as a SW or HW components, and the implementation itself is performed at a late stage of the development process. The partition is based on the optimisation of the application’s and components’ extra-functional properties (EFPs) that are derived from the requirements and project constraints. For the optimization a Multiple Criteria Decision Analysis (MCDA) method is used. As a part of the main contribution, the thesis includes several independent contributions that are of a more general character: a) modeling principles for component-based applications which consists of SW and HW components, and a component can be implemented as SW or/and HW code; b) a classification and analysis of EFPs in respect to the dependency on their HW or SW implementation; c) composition rules for some of EFPs for SW and HW components; d) suitability and limitations of MCDA methods in their usage for the partitioning decisions. MULTIPAR is also implemented in a form of a tool that enables a selection of components and analysis of the system in respect to the selected EFPs. The feasibility of MULTIPAR was validated through two industrial cases. The thesis is organized in two parts; the first part includes an introduction summarizing the overall work and discussing the research approach, and the second part collect the most relevant papers published in different venues.
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| 5. |
- Lednicki, Luka
(författare)
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Software and hardware models in component-based development of embedded systems
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- As modern embedded systems grow in complexity component-based development is an increasingly attractive approach to make the development of such systems simpler and less error prone. In this approach software systems are built by composing them out of prefabricated software components. One of the challenges for applying component-based development to embedded systems is the tight coupling between the software and the hardware platform. To take full advantage of the component-based approach in the embedded domain, the development process has to provide support for describing and handling this coupling.The goal of this thesis is to provide advancements in development of embedded component-based systems by using a combination of software and hardware models. To achieve the overall research goal, three different aspects are investigated: (i) how to provide support for integration of sensors and actuators in component-based development, (ii) how to utilize a combination of software and hardware models in development of distributed systems, and (iii) how to analyze extra-functional system properties using models of both software and hardware. The thesis goal is addressed by following contributions: (i) a component-based model which allows describing sensors and actuators, and how they are connected to the processing nodes and software components, (ii) a method for automatic synthesis of code for communication with sensors and actuators, (iii) a framework for automatic generation of distributed communication in component-based models and (iv) a compositional model-level analysis of timing and processing node utilization for component-based applications. These contributions are evaluated in separation, by applying prototype tools to either example systems, case-studies, or test scenarios.
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