A Process-oriented Approach for Migrating Software to Heterogeneous Platforms

Context: Heterogeneous computing, i.e., computing performed on processors of different types - such as combination of CPUs and GPUs, or CPUs and FPGAs - has shown to be a feasible path towards higher performance and less energy consumption. However, this approach imposes a number of challenges on the software side that must be addressed in order to achieve the aforementioned advantages.Objective: The objective of this thesis is to improve the process of software deployment on heterogeneous platforms. Through a detailed analysis of the state-of-the-art and state-of-the-practice, we aim to provide a reasoning framework for engineers to migrate software to be executed on such platforms.Method: To achieve our goal, we conducted: (i) a literature review in the form of a systematic mapping study on software deployment on heterogeneous platforms; (ii) a multiple case study in industry that highlights the main challenges and concerns in the state-of-the-practice in the area; and (iii) a study in which we propose and evaluate a decision framework to guide engineers in migrating software for execution on heterogeneous platforms, with a case study in the automotive domain.Results: In the mapping study, we provided a thorough classification of the identified concerns and approaches to deploying software on heterogeneous platforms. Among other findings, we discovered a lack of holistic approaches that include development processes, as well as few validation studies in industrial contexts. In the second study, we discovered and analyzed common practices and challenges that companies face when using heterogeneous platforms. One of such challenges is related to the lack of approaches that cover the software development lifecycle. In the third study, we proposed a decision framework that guides engineers in the process of reasoning for migrating software for execution on heterogeneous platforms. It consists of five stages (assessing, re-architecting, developing, deploying, evaluating), each containing a set of aspects to be addressed through the answers to predefined questions.Conclusions: This thesis addresses a gap that was identified in both theory and practice concerning the lack of holistic approaches to migrate software for execution on heterogeneous platforms. Our proposed approach addresses the problem through systematic guidance for engineers.Future work: In the future, we intend to further refine the proposed framework through case studies in domains other than automotive. We will explore its integration with existing software engineering processes in industrial contexts, performing in-depth analysis of the required adaptations and providing detailed solutions within the stages of the framework

Software Concerns for Execution on Heterogeneous Platforms

Context: Heterogeneous computing, i.e., computing performed on different types of execution units, such as CPUs, GPUs, FPGAs, has shown to be a feasible path towards higher performance and less energy consumption. Heterogeneous platforms are specialized on specific types of computation, e.g., parallel computing. However, this approach imposes a number of challenges on the software side. One of such challenges is related to software deployment, in which applications must be prepared to be executed in different target architectures. Further, the approach demands a robust inter-process communication solution, since these systems inherently distribute computation. Objective: The objective of this thesis is twofold. First, to provide an overview of the state-of-the-art of software deployment on heterogeneous platforms, with emphasis to goals, concerns, challenges, and identification of topics of importance for further research. Second, to investigate the communication problem and propose a novel method that improves inter-process communication in distributed systems. Method: Six papers were written as results of four studies: (i) a literature review in the form of a systematic mapping study on software deployment on heterogeneous platforms; (ii) a systematic evaluation of deployment methods in the context of a self-driving heavy vehicle; (iii) an investigation on data marshalling approaches and how they perform in the context of a cyber-physical system; and (iv) a novel message restructuring approach, also in the context of cyber-physical systems. Results and Conclusions: The mapping study discussed the (i) concerns on the topic such as scheduling and software quality; the (ii) approaches available, such as frameworks; and the (iii) architecture solutions used, such as styles and principles. In the second study, we found that the performance decay is negligible when using sandboxed environments for deployment. In the third and fourth studies, we proposed and evaluated a data marshalling approach that decreases bandwidth consumption. Future work: We intend to identify challenges that are currently faced in an industrial setting. In particular, a migration from a non-heterogenous platform to a heterogeneous platform can be studied in the context of a modern software development process, such as DevOps

Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms

The most important way to achieve higher performance in computer systems is through heterogeneous computing, i.e., by adopting hardware platforms containing more than one type of processor, such as CPUs, GPUs, and FPGAs. Several types of algorithms can be executed significantly faster on a heterogeneous platform. However, migrating CPU-executable software to other types of execution platforms poses a number of challenges to software engineering. Significant efforts are required in such type of migration, particularly for re-architecting and re-implementing the software. Further, optimizing it in terms of performance and other runtime properties can be very challenging, making the process complex, expensive, and errorprone. Therefore, a systematic approach based on explicit and justified architectural decisions is needed for a successful refactoring process from a homogeneous to a heterogeneous platform. In this paper, we propose a decision framework that supports engineers when refactoring software systems to accommodate heterogeneous platforms. It includes the assessment of important factors in order to minimize the risk of recurrent problems in the process. Through a set of questions, practitioners are able to formulate answers that will help in making appropriate architectural decisions to accommodate heterogeneous platforms. The contents of the framework have been developed and evolved based on discussions with architects and developers in the automotive domain

Continuous Experimentation and the cyber-physical systems challenge: An overview of the literature and the industrial perspective.

Context: New software development patterns are emerging aiming at accelerating the process of delivering value. One is Continuous Experimentation, which allows to systematically deploy and run instrumented software variants during development phase in order to collect data from the field of application. While currently this practice is used on a daily basis on web-based systems, technical difficulties challenge its adoption in fields where computational resources are constrained, e.g., cyber-physical systems and the automotive industry. Objective: This paper aims at providing an overview of the engagement on the Continuous Experimentation practice in the context of cyber-physical systems.Method: A systematic literature review has been conducted to investigate the link between the practice and the field of application. Additionally, an industrial multiple case study is reported. Results: The study presents the current state-of-the-art regarding Continuous Experimentation in the field of cyber-physical systems. The current perspective of Continuous Experimentation in industry is also reported. Conclusions: The field has not reached maturity yet. More conceptual analyses are found than solution proposals and the state-of-practice is yet to be achieved. However it is expected that in time an increasing number of solutions will be proposed and validated

Investigating Software Deployment on Heterogeneous Platforms

Devices with computing capabilities are everywhere. Physical components that once were restricted to its forms and mechanics to provide functionality have now gained an enormous number of possibilities through the implementation of Embedded Systems (ES). However, together with the advantages of ES come the challenges of dealing with both the increasing complexity of software and the different constraints of hardware. Moreover, it is becoming a common practice to deploy software on computation units of different types (i.e. CPUs, GPUs and FPGAs) in order to optimize data processing and resource utilization. This paper reports on a PhD research project in the area of software deployment on heterogeneous platforms, focusing on how different deployment strategies contribute to achieve certain non-functional properties, such as performance and energy efficiency. As it is important to understand previous practices and acknowledge possible gaps in the research area, a systematic literature review is currently being conducted, and its initial/planning stages are described. Further, recent contributions in the context of data marshalling are also discussed, as well as the planned next steps and the impact of this project in an industrial context

A Review on Software Architectures for Heterogeneous Platforms

The increasing demands for computing performance have been a reality regardless of the requirements for smaller and more energy efficient devices. Throughout the years, the strategy adopted by industry was to increase the robustness of a single processor by increasing its clock frequency and mounting more transistors so more calculations could be executed. However, it is known that the physical limits of such processors are being reached, and one way to fulfill such increasing computing demands has been to adopt a strategy based on heterogeneous computing, i.e., using a heterogeneous platform containing more than one type of processor. This way, different types of tasks can be executed by processors that are specialized in them. Heterogeneous computing, however, poses a number of challenges to software engineering, especially in the architecture and deployment phases. In this paper, we conduct an empirical study that aims at discovering the state-of-the-art in software architecture for heterogeneous computing, with focus on deployment. We conduct a systematic mapping study that retrieved 28 studies, which were critically assessed to obtain an overview of the research field. We identified gaps and trends that can be used by both researchers and practitioners as guides to further investigate the topic

Architectural Bad Smells in Software Product Lines: An Exploratory Study

The Software Product Lines (SPL) paradigm has arisen for taking advantage of existing common aspects between different products, while also considering product-specific features. The architecture of a SPL comprises a model that will result in product architectures, and may include solutions leading to bad (architectural) design. One way to assess such design decisions is through the identification of architectural bad smells, which are properties that prejudice the overall software quality, but are not necessarily faulty or errant.Inthis paper, we conduct an exploratory study that aims at characterizing bad smells in the context of product line architectures. We analyzed an open source SPL project and extracted its architecture to investigate the occurrence or absence of four smells initially studied in single systems. In addition, we propose a smell specific to the SPL context and discuss possible causes and implications of having those smells in the architecture of a product line. The results indicate that the granularity of the SPL features may influence on the occurrence of smells. Copyright \ua9 2014 ACM 978-1-4503-2523-3/14/04 $15.00

Architectural Bad Smells in Software Product Lines: An Exploratory Study

The Software Product Lines (SPL) paradigm has arisen for taking advantage of existing common aspects between different products, while also considering product-specific features. The architecture of a SPL comprises a model that will result in product architectures, and may include solutions leading to bad (architectural) design. One way to assess such design decisions is through the identification of architectural bad smells, which are properties that prejudice the overall software quality, but are not necessarily faulty or errant.Inthis paper, we conduct an exploratory study that aims at characterizing bad smells in the context of product line architectures. We analyzed an open source SPL project and extracted its architecture to investigate the occurrence or absence of four smells initially studied in single systems. In addition, we propose a smell specific to the SPL context and discuss possible causes and implications of having those smells in the architecture of a product line. The results indicate that the granularity of the SPL features may influence on the occurrence of smells. Copyright \ua9 2014 ACM 978-1-4503-2523-3/14/04 $15.00

Software Deployment on Heterogeneous Platforms: A Systematic Mapping Study

Context: Multiple types of processing units (e.g., CPUs, GPUs and FPGAs) can be used jointly to achieve better performance in computational systems. However, these units are built with fundamentally different characteristics and demand attention especially towards software deployment. Objective: The goal of this work is to summarize the state-of-the-art of software deployment on heterogeneous platforms. We provide an overview of the research area by searching for and categorizing relevant studies, as well as discussing gaps and trends of the field. We are interested in the main concerns (RQ1) and the approaches used (RQ2) when deploying software on heterogeneous platforms. Method: In order to achieve our goal, we performed a systematic mapping study, which refers to a method for reviewing literature with basis on predefined search strategies and a multi-step selection process. Results: We selected and analyzed 146 primary studies from multiple sources and found that the area of research is dominated by solution proposals. The majority of the studies discuss concerns about scheduling, the quality of the software, and its architecture. A large number of studies focuses on the problem of scheduling tasks and processes. We found approaches that are applied at different binding times (i.e., design time, runtime, orthogonal). Conclusion: The evaluation of the proposed solutions in an industrial context is missing. Also, the proposed methods have not been evaluated in development processes. Most of the methods address a particular concern, or a few concerns, while there is a lack of a holistic approach