| 1. |
- Campeanu, Gabriel, 1982-
(författare)
-
GPU Support for Component-based Development of Embedded Systems
- 2018
-
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).
|
|
| 2. |
- Ciccozzi, Federico, 1983-, et al.
(författare)
-
Editorial to theme issue on model-driven engineering of component-based software systems
- 2019
-
Ingår i: Software and Systems Modeling. - : Springer Science and Business Media LLC. - 1619-1374 .- 1619-1366. ; 18:1, s. 7-10
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This theme issue aims at providing a forum for disseminating latest trends in the use and combination of model-driven engineering (MDE) and component-based software engineering (CBSE). One of the main aims of MDE is to increase productivity in the development of complex systems, while reducing the time to market. Regarding CBSE, one of the main goals is to deliver and then support the exploitation of reusable “off-the-shelf” software components to be incorporated into larger applications. An effective interplay of MDE and CBSE can bring benefits to both communities: on the one hand, the CBSE community would benefit from implementation and automation capabilities of MDE, and on the other hand, MDE would benefit from the foundational nature of CBSE. In total, we received 23 submissions to this theme issue, and each submission was reviewed by at least three reviewers. Thanks to the high quality of the submissions that we received, we could eventually accept six papers for publication.
|
|
| 3. |
- Inam, Rafia, 1974-, et al.
(författare)
-
Virtual Node - To Achieve Temporal Isolation and Predictable Integration of Real-Time Components
- 2012
-
Ingår i: International Journal on Computing (JoC). - : Global Science and Technology Forum (GSTF). - 2010-2283. ; 1:4, s. 63-69
-
Tidskriftsartikel (refereegranskat)abstract
- We present an approach of two-level deployment process for component models used in distributed real-time embedded systems to achieve predictable integration of real-time components. Our main emphasis is on the new concept of virtual node with the use of a hierarchical scheduling technique. Virtual nodes are used as means to achieve predictable integration of software components with real-time requirements. The hierarchical scheduling framework is used to achieve temporal isolation between components (or sets of components). Our approach permits detailed analysis, e.g., with respect to timing, of virtual nodes and this analysis is also reusable with the reuse of virtual nodes. Hence virtual node preserves real-time properties across reuse and integration in different contexts.
|
|
| 4. |
- Axelsson, Jakob, et al.
(författare)
-
Towards the architecture of a decision support ecosystem for system component selection
- 2017
-
Ingår i: 11th Annual IEEE International Systems Conference, SysCon 2017 - Proceedings. - 9781509046225 - 9781509046232
-
Konferensbidrag (refereegranskat)abstract
- When developing complex software-intensive systems, it is nowadays common practice to base the solution partly on existing software components. Selecting which components to use becomes a critical decision in development, but it is currently not well supported through methods and tools. This paper discusses how a decision support system for this problem could benefit from a software ecosystem approach, where participants share knowledge across organizations both through reuse of analysis models, and through partially disclosed past decision cases. We show how the ecosystem architecture becomes fundamental to deal with efficient knowledge sharing, while respecting constraints on integrity of intellectual property. A concrete architecture proposal is outlined, which is a web-based distributed system-of-systems. Experiences of a proof-of-concept implementation are also described.
|
|
| 5. |
- Bilic, Damir, et al.
(författare)
-
Detecting inconsistencies in annotated product line models
- 2020
-
Ingår i: SPLC '20: Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A. - New York, NY, USA : Association for Computing Machinery. - 9781450375696 ; , s. 252-262
-
Konferensbidrag (refereegranskat)abstract
- Model-based product line engineering applies the reuse practices from product line engineering with graphical modeling for the specification of software intensive systems. Variability is usually described in separate variability models, while the implementation of the variable systems is specified in system models that use modeling languages such as SysML. Most of the SysML modeling tools with variability support, implement the annotation-based modeling approach. Annotated product line models tend to be error-prone since the modeler implicitly describes every possible variant in a single system model. To identifying variability-related inconsistencies, in this paper, we firstly define restrictions on the use of SysML for annotative modeling in order to avoid situations where resulting instances of the annotated model may contain ambiguous model constructs. Secondly, inter-feature constraints are extracted from the annotated model, based on relations between elements that are annotated with features. By analyzing the constraints, we can identify if the combined variability- and system model can result in incorrect or ambiguous instances. The evaluation of our prototype implementation shows the potential of our approach by identifying inconsistencies in the product line model of our industrial partner which went undetected through several iterations of the model.
|
|
| 6. |
- Campeanu, Gabriel, et al.
(författare)
-
A GPU-aware Component Model Extension for Heterogeneous Embedded Systems
- 2015
-
Ingår i: The Tenth International Conference on Software Engineering Advances ICSEA 2015. - 9781612084381
-
Konferensbidrag (refereegranskat)abstract
- One way for modern embedded systems to tackle the demand for more complex functionality requiring more computational power is to take advantage of heterogeneous hardware. These hardware platforms are constructed from the combination of different processing units including both traditional CPUs and for example Graphical Processing Units (GPUs). However, there is a lack of efficient approaches supporting software development for such systems. In particular, modern software development approaches, such as component-based development, do not provide sufficient support for heterogeneous hardware platforms. This paper presents a component model extension, which defines specific features for components with GPU capabilities. The benefits of the proposed solution include an increased system performance by accelerating the communication between GPU-aware components and the possibility to control the distribution of GPU computation resources at system level.
|
|
| 7. |
- Campeanu, Gabriel, et al.
(författare)
-
Allocation Optimization for Component-based Embedded Systems with GPUs
- 2018
-
Ingår i: 44th Euromicro Conference on Software Engineering and Advanced Applications SEAA 2018. - 9781538673829 ; , s. 101-110
-
Konferensbidrag (refereegranskat)abstract
- Platforms equipped with GPU processors help mitigating the ever-increasing computational demands of modern embedded systems. Such systems can be specifically developed by using component-based development thanks to the concept of flexible components. Through this concept, a component can be transparently executed either on a CPU or a GPU. However, this flexibility complicates the allocation process because it adds additional complexity (i.e., due to the undecided CPU or GPU execution) and constraints to consider (i.e., CPUs and GPUs properties). In this work, we address this problem by providing an optimization model for component-based embedded systems executing on both CPU and GPU. The model addresses important optimization goals, characteristic to the embedded system domain, such as memory usage, energy usage and execution time. A novelty of this work is the formal description of the optimization model, which supports the usage of mixed integer nonlinear programming to compute optimal allocation schemes. To examine the feasibility of the proposed method, we apply the optimization model on a vision system constructed using the industrial Rubus component model.
|
|
| 8. |
- Campeanu, Gabriel, et al.
(författare)
-
Developing CPU-GPU Embedded Systems using Platform-Agnostic Components
- 2017
-
Ingår i: Proceedings - 43rd Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2017. - 9781538621400 ; , s. 176-180
-
Konferensbidrag (refereegranskat)abstract
- Nowadays, there are many embedded systems with different architectures that have incorporated GPUs. However, it is difficult to develop CPU-GPU embedded systems using component-based development (CBD), since existing CBD ap- proaches have no support for GPU development. In this context, when targeting a particular CPU-GPU platform, the component developer is forced to construct hardware-specific components, which are problematic to (re-)use in different contexts. More- over, hard-coding specific GPU-usage characteristics (e.g., the number of utilized GPU threads) inside the component is not possible without making detailed assumptions about the system in which the component is used, which conflicts with separation- of-concerns CBD principle. The paper presents a solution to allow component-based development of platform-agnostic CPU-GPU embedded systems through: i) high-level API, ii) adapters, and iii) code template. The API abstracts the specifics of the different platforms, while the adapters externalize hardware-specific activities outside components. We also raise the decision regarding the GPU- usage specifications, from the component to the system level. Furthermore, to minimize the development effort, we provide a code template that contains ready-made code fragments required for GPU development. As a case study, we examine the feasibility of our solution applied on a component-based vision system of an underwater robot.
|
|
| 9. |
- Campeanu, Gabriel, et al.
(författare)
-
Flexible Components for Development of Embedded Systems with GPUs
- 2017
-
Ingår i: 24th Asia-Pacific Software Engineering Conference APSEC 2017. - 9781538636817 ; , s. 219-228
-
Konferensbidrag (refereegranskat)abstract
- Today, embedded systems incorporate GPUs through a multitude of different architectures. When it comes to the development of these systems with GPUs, component-based development is ill-equipped as it does not provide support for GPUs. Instead, the component developer needs to encapsulate inside the component, besides functionality, settings and environment information that are specific to a particular GPU architecture. This binds the component this GPU architecture. Using these hardware-specific components characterized by restricted reusability, the system developer is confined to a limited design space which may negatively impact the overall system feasibility. In this paper, we introduce the concept of flexible components, which are components that can be executed indifferently on CPU or GPU, regardless of the architecture. Using flexible components, component developers are relieved from the side development activities (e.g., environment information) which are automatically handled by component-level mechanisms. To enhance component communications, connection elements (i.e., adapters) are generated to handle component data transmission, taking in consideration the platform characteristics. Finally, our proposed solution is evaluated by using flexible components to implement the vision system of an underwater robot, and execute it on three platforms with different GPU architectures.
|
|
| 10. |
- Campeanu, Gabriel, 1982-
(författare)
-
GPU-aware Component-based Development for Embedded Systems
- 2016
-
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.
|
|
