A Federated Simulation Environment for Hybrid Systems

Gayen, Saurabh; Tyson, Eric J.; Franklin, Mark A.; Chamberlain, Roger D.

doi:10.1109/pads.2007.5

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…In practice, a pipelined architecture [15] allows the software to be represented as general data flow graphs, with particular focus on the performance. The approach bases the allocation strategy on the simulation of executing these graphs.…”

Section: Determining the Overall Architecture Designmentioning

confidence: 99%

Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms

Andrade

Crnković

Bosch

2020

2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)

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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.

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Section: Determining the Overall Architecture Designmentioning

confidence: 99%

Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms

Andrade

Crnković

Bosch

2020

2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)

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“…Architecture design: Two key aspects have been addressed when designing the architecture [25,26]: communication and computation. One way to practically address them is through the separation of concerns technique, setting "communication" and "computation" as the main concerns in the center.…”

Section: Related Workmentioning

confidence: 99%

“…CPU), and one or more accelerators (e.g., GPU for highly parallelized tasks). Alternatively, a pipelined architecture can be implemented, allowing software to be represented as general data flow graphs [26], with particular focus on the performance. The approach bases the allocation strategy on the simulation of executing these graphs.…”

Section: Related Workmentioning

confidence: 99%

HPM-Frame: A Decision Framework for Executing Software on Heterogeneous Platforms

Andrade¹,

Benderius²,

Berger³

et al. 2020

Preprint

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Heterogeneous computing is one of the most important computational solutions to meet rapidly increasing demands on system performance. It typically allows the main flow of applications to be executed on a CPU while the most computationally intensive tasks are assigned to one or more accelerators, such as GPUs and FPGAs. The refactoring of systems for execution on such platforms is highly desired but also difficult to perform, mainly due the inherent increase in software complexity. After exploration, we have identified a current need for a systematic approach that supports engineers in the refactoring process-from CPU-centric applications to software that is executed on heterogeneous platforms. In this paper, we introduce a decision framework that assists engineers in the task of refactoring software to incorporate heterogeneous platforms. It covers the software engineering lifecycle through five steps, consisting of questions to be answered in order to successfully address aspects that are relevant for the refactoring procedure. We evaluate the feasibility of the framework in two ways. First, we capture the practitioner's impressions, concerns and suggestions through a questionnaire. Then, we conduct a case study showing the step-by-step application of the framework using a computer vision application in the automotive domain.

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“…The Auto-Pipe tool set includes an X language compiler, called X-Com [7], the X-Sim federated simulation environment [8], and the X-Dep deployment tool [4]. These components are the basis of the archetypical Auto-Pipe design flow depicted in Figure 5.…”

Section: Auto-pipe Tool Setmentioning

confidence: 99%

“…Auto-Pipe [7] is a tool set that supports application development of streaming computations on architecturally diverse systems. Auto-Pipe enables an application developer to: 1) author the application using the language(s) of his/her choice for expressing kernel computations and a coordination language, called X, to express the streaming topology; 2) model the application using a federated simulation system [8]; and 3) deploy the application on a diverse architecture [4].…”

Section: Introductionmentioning

confidence: 99%

Application-guided tool development for architecturally diverse computation

Chamberlain

Buhler

Franklin

et al. 2010

Proceedings of the 2010 ACM Symposium on Applied Computing

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Architecturally diverse computation exploits non-traditional computing platforms (e.g., field-programmable gate arrays, graphics processors, heterogeneous chip multiprocessors) to execute user applications. We have designed the Auto-Pipe tool set with the goal of easing the task of developing applications for architecturally diverse systems. Prior to and during the course of Auto-Pipe's design, we have developed a number of real, substantial applications, and the the lessons learned during the development of these applications has had a direct bearing on the capabilities of Auto-Pipe. In this paper, we describe the relationship between our application development experience and Auto-Pipe. In short, how have applications guided the tools' evolution and development?Monte Carlo simulation, encryption, computational finance, computational biology, computational astrophysics, approximate text search, application development tools

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A Federated Simulation Environment for Hybrid Systems

Cited by 10 publications

References 10 publications

Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms

Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms

HPM-Frame: A Decision Framework for Executing Software on Heterogeneous Platforms

Application-guided tool development for architecturally diverse computation

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