TY - JOUR T1 - Automated Model-based Optimization of Data-Adaptable Embedded Systems JF - ACM Transactions on Embedded Computing Systems Y1 - 2019 A1 - Adrian Lizarraga A1 - Jonathan Sprinkle A1 - Roman Lysecky AB -

This paper presents a modeling and optimization framework that enables developers to model an application's data sources, tasks, and exchanged data tokens; specify application requirements through high-level design metrics and fuzzy logic based optimization rules; and define an estimation framework to automatically optimize the application at runtime. We demonstrate the modeling and optimization process via an example application for video-based vehicle tracking and collision avoidance. We analyze the benefits of runtime optimization by comparing the performance of static point solutions to dynamic solutions over five distinct execution scenarios, showing improvements of up to 74% for dynamic over static configurations.

VL - 19 UR - https://doi.org/10.1145/3372142 IS - 1 ER - TY - CONF T1 - WiP Abstract: String stability of commercial adaptive cruise control vehicles T2 - International Conference on Cyber-Physical Systems Y1 - 2019 A1 - George Gunter A1 - Y. Yang A1 - Raphael E Stern A1 - Daniel B. Work A1 - Maria Laura Dell Monache A1 - Rahul Bhadani A1 - Matt Bunting A1 - Roman Lysecky A1 - Jonathan Sprinkle A1 - Benjamin Seibold A1 - Benedetto Piccoli KW - Adaptive Cruise Control KW - String Stability AB - In this work, we conduct a series of car-following experiments with seven different ACC vehicles and use the collected data to model the car-following behavior of each vehicle. Using a linear stability analysis, the string stability of each tested vehicle is analyzed. Addition- ally, platoon experiments with platoons of up to eight identical vehicles are conducted to validate the stability findings. Previously, only one commercial ACC system has been evaluated for string stability. JF - International Conference on Cyber-Physical Systems UR - https://dl.acm.org/citation.cfm?id=3313325 ER - TY - JOUR T1 - Task Transition Scheduling for Data-Adaptable Systems JF - ACM Transactions on Embedded Computing Systems (TECS) Y1 - 2017 A1 - Nathan Sandoval A1 - Casey Mackin A1 - Sean Whitsitt A1 - Gopinath, Vijay Shankar A1 - Sachidanand Mahadevan A1 - Milakovich, Andrew A1 - Merry, Kyle A1 - Jonathan Sprinkle A1 - Roman Lysecky KW - Data adaptability KW - hardware/software codesign KW - model-based design KW - runtime transition scheduling AB -

Data-adaptable embedded systems operate on a variety of data streams, which requires a large degree of configurability and adaptability to support runtime changes in data stream inputs. Data-adaptable reconfigurable embedded systems, when decomposed into a series of tasks, enable a flexible runtime implementation in which a system can transition the execution of certain tasks between hardware and software while simultaneously continuing to process data during the transition. Efficient runtime scheduling of task transitions is needed to optimize system throughput and latency of the reconfiguration and transition periods. In this article, we provide an overview of a runtime framework enabling the efficient transition of tasks between software and hardware in response to changes in system inputs. We further present and analyze several runtime transition scheduling algorithms and highlight the latency and throughput tradeoffs for two data-adaptable systems. To evaluate the task transition selection algorithms, a case study was performed on an adaptable JPEG2000 implementation as well as three other synchronous dataflow systems characterized by transition latency and communication load.

VL - 16 UR - http://doi.acm.org/10.1145/3047498 ER - TY - Generic T1 - Model-based Fuzzy Logic Classifier Synthesis for Optimization of Data-Adaptable Embedded Systems T2 - International Conference on InfoSymbiotics/DDDAS, 2016 Y1 - 2016 A1 - Adrian Lizarraga A1 - Roman Lysecky A1 - Jonathan Sprinkle JF - International Conference on InfoSymbiotics/DDDAS, 2016 CY - Hartford, CT ER - TY - CONF T1 - Model-Driven Optimization of Data-Adaptable Embedded Systems T2 - 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC) Y1 - 2016 A1 - Adrian Lizarraga A1 - Roman Lysecky A1 - Jonathan Sprinkle JF - 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC) PB - IEEE ER - TY - CONF T1 - Model-driven Optimization of Data-Adaptable Embedded Systems T2 - COMPSAC Y1 - 2016 A1 - Adrian Lizarraga A1 - Roman Lysecky A1 - Jonathan Sprinkle AB -

Complex sensing and decision applications such as object tracking and classification, video surveillance, unmanned aerial vehicle flight decisions, and others operate on vast data streams with dynamic characteristics. As the availability and quality of the sensed data changes, the underlying models and decision algorithms should continually adapt in order to meet desired high-level requirements. Due to the complexity of such dynamic data-driven systems, traditional design time techniques are often incapable of producing a solution that remains optimal in the face of dynamically changing data, algorithms, and even availability of computational resources. To assist developers of these systems, we present a modeling and optimization methodology that enables developers to capture application task flows and data sources, define associated quality metrics with data types, specify each algorithm’s data and quality requirements, and define a data quality estimation framework to optimize the application at runtime. We demonstrate each facet of the modeling and optimization process via a video-based vehicle tracking and collision avoidance application, and show how such an approach results in efficient design space exploration when selecting the optimal set of algorithm modalities. When searching for an application configuration within 1% to 5% of optimal, our model-guided approach can achieve speedups of up to 9.3X versus a standard genetic algorithm and speedups of up to 80X relative to a brute force algorithm.

JF - COMPSAC PB - IEEE UR - http://dx.doi.org/10.1109/COMPSAC.2016.156 ER - TY - CONF T1 - Generating Model Transformations for Mending Dynamic Constraint Violations in Cyber Physical Systems T2 - The 14th Workshop on Domain-Specific Modeling Y1 - 2014 A1 - Sean Whitsitt A1 - Jonathan Sprinkle A1 - Roman Lysecky AB -

Cyber physical systems by definition involve design constraints addressing the computation and communication necessary to control physical systems. These systems have been modeled using domain specific modeling languages, but some limitations exist in the continued application of such a modeling approach to more complex, or safety-critical, systems. Specifically, it is well known how to formulate constraints in a domain-specific modeling language in order to prevent users from building invalid structures, but existing constraint-based techniques do not take into consideration design requirements that may require analysis in the physical domain (i.e. dynamic constraints). Those analysis results, when interpreted by a domain expert, can inform changes to the model: unfortunately, this process does not scale. This paper presents an approach to integrating dynamic constraints that cannot be enforced using structural model constraints. The technique uses expert blocks to analyze systems and generates model transformations specific to the system using the results of those analyses to fix constraint violations. The paper describes a Dynamic Constraint Feedback (DCF) methodology for integrating this technique into existing systems from a generic perspective. Specific examples in this paper are derived from the domain of data adaptable reconfigurable embedded systems (DARES).

JF - The 14th Workshop on Domain-Specific Modeling UR - http://dx.doi.org/10.1145/2688447.2688454 ER - TY - CONF T1 - Efficient Reconfiguration Methods to Enable Rapid Deployment of Runtime Reconfigurable Systems T2 - Asilomar Conference on Signals, Systems and Computers Y1 - 2013 A1 - Roman Lysecky A1 - Nathan Sandoval A1 - Sean Whitsitt A1 - Casey Mackin A1 - Jonathan Sprinkle JF - Asilomar Conference on Signals, Systems and Computers PB - IEEE CY - Pacific Grove, CA UR - http://dx.doi.org/10.1109/ACSSC.2013.6810401 ER - TY - CONF T1 - How You Can Learn to Stop Worrying and Love Reconfigurable Embedded Systems: A Tutorial T2 - Engineering of Computer Based Systems (ECBS), 2013 20th IEEE International Conference and Workshops on the Y1 - 2013 A1 - Nathan Sandoval A1 - Casey Mackin A1 - Roman Lysecky A1 - Jonathan Sprinkle KW - C++ language KW - C/C++ code KW - codesign KW - Computers KW - Conferences KW - data streams KW - embedded hardware KW - embedded systems KW - Hardware KW - hardware tasks KW - hardware-software codesign KW - image processing algorithms KW - JPEG2000 standards KW - middleware KW - middleware framework KW - modeling infrastructure KW - reconfigurable embedded systems KW - runtime behaviors KW - software tasks KW - software tool KW - software tools KW - Transform coding KW - Tutorials JF - Engineering of Computer Based Systems (ECBS), 2013 20th IEEE International Conference and Workshops on the ER - TY - CONF T1 - Model Based Development with the Skeleton Design Method T2 - 20th IEEE International Conference and Workshops on the Engineering of Computer Based Systems Y1 - 2013 A1 - Sean Whitsitt A1 - Jonathan Sprinkle A1 - Roman Lysecky JF - 20th IEEE International Conference and Workshops on the Engineering of Computer Based Systems UR - http://dx.doi.org/10.1109/ECBS.2013.16 ER - TY - CONF T1 - Runtime Hardware/Software Task Transition Scheduling for Runtime-Adaptable Embedded Systems T2 - International Conference on Field-Programmable Technology (ICFPT) Y1 - 2013 A1 - Nathan Sandoval A1 - Casey Mackin A1 - Sean Whitsitt A1 - Roman Lysecky A1 - Jonathan Sprinkle JF - International Conference on Field-Programmable Technology (ICFPT) UR - http://dx.doi.org/10.1109/FPT.2013.6718382 ER - TY - CONF T1 - System Throughput Optimization and Runtime Communication Middleware Supporting Dynamic Software-Hardware Task Migration in Data Adaptable Embedded Systems T2 - Engineering of Computer Based Systems (ECBS), 2013 20th IEEE International Conference and Workshops on the Y1 - 2013 A1 - Nathan Sandoval A1 - Casey Mackin A1 - Sean Whitsitt A1 - Roman Lysecky A1 - Jonathan Sprinkle KW - combinatorial explosion KW - Data adaptability KW - data adaptable design methodology KW - data adaptable embedded systems KW - data configurations KW - data handling KW - Data models KW - data profile correlation KW - design time optimization KW - dynamic software-hardware task migration KW - embedded systems KW - Field programmable gate arrays KW - FIFO queues KW - Firing KW - Hardware KW - hardware accelerators KW - hardware-software codesign KW - hardware-software communication wrapper KW - hardware/software codesign KW - hardware/software communication middleware KW - heuristic programming KW - heuristic search methodology KW - middleware KW - model-based design KW - Pareto optimal configurations KW - Pareto optimisation KW - Runtime KW - runtime communication middleware KW - search problems KW - simulation-based methodology KW - system throughput optimization JF - Engineering of Computer Based Systems (ECBS), 2013 20th IEEE International Conference and Workshops on the ER - TY - CONF T1 - Automated Software Generation and Hardware Coprocessor Synthesis for Data-Adaptable Reconfigurable Systems T2 - Engineering of Computer Based Systems (ECBS), 2012 IEEE 19th International Conference and Workshops on Y1 - 2012 A1 - Milakovich, Andrew A1 - Vijay Gopinath A1 - Roman Lysecky A1 - Jonathan Sprinkle KW - Data adaptability KW - hardware/software codesign KW - model-based design AB -

We present an overview of a data-adaptable reconfigurable embedded systems design methodology. The paper presents a novel paradigm for hardware/software code sign and reconfigurable computing driven by data-adaptability. The data-adaptable approach allows designers to directly model the data configurability of the target application, thereby enabling a solution that permits dynamic reconfiguration based on the data profile of the incoming data stream. This approach permits low-power, small form-factor hardware implementations of algorithms that might otherwise consume significant resources, or perhaps exceed the available space of the reconfigurable hardware.

JF - Engineering of Computer Based Systems (ECBS), 2012 IEEE 19th International Conference and Workshops on UR - http://dx.doi.org/10.1109/ECBS.2012.16 ER - TY - CONF T1 - An Overseer Control Methodology for Data Adaptable Embedded Systems T2 - International Workshop on Multi-Paradigm Modeling (MPM) Y1 - 2012 A1 - Sean Whitsitt A1 - Jonathan Sprinkle A1 - Roman Lysecky JF - International Workshop on Multi-Paradigm Modeling (MPM) UR - http://dx.doi.org/10.1145/2508443.2508448 ER - TY - CONF T1 - Hardware/Software Communication Middleware for Data Adaptable Embedded Systems T2 - Proceedings of the 18th IEEE International Conference and Workshops on Engineering of Computer-Based Systems Y1 - 2011 A1 - Sachidanand Mahadevan A1 - Vijay Gopinath A1 - Roman Lysecky A1 - Jonathan Sprinkle A1 - Jerzy Rozenblit A1 - Michael Marcellin AB -

Recent trends toward increased flexibility and configurability in emerging applications present demanding challenges for implementing systems that incorporate such capabilities. The resulting application configuration space is generally much larger than any one hardware implementation can support. We provide an overview of a new data-adaptive approach to the rapid design and implementation of such highly configurable applications. In support of this data-adaptable approach, we present and detail an efficient and flexible hardware/software communication middleware to support the seamless communication between hardware and software tasks at runtime. We highlight the flexibility of this interface and present an initial case study and results demonstrating the performance capabilities and area requirements.

JF - Proceedings of the 18th IEEE International Conference and Workshops on Engineering of Computer-Based Systems PB - IEEE Computer Society Press UR - http://dx.doi.org/10.1109/ECBS.2011.12 ER - TY - CONF T1 - Modeling of Data Adaptable Reconfigurable Embedded Systems T2 - Proceedings of the 8th IEEE Workshop on Model-Based Development for Computer-Based Systems Y1 - 2011 A1 - Vijay Gopinath A1 - Jonathan Sprinkle A1 - Roman Lysecky AB -

Many applications require high flexibility, high configurability and high processing speeds. The physical constraints of a highly flexible system’s hardware implementation preclude a hardware solution that satisfies all configuration options. Similarly for pure software implementations, even if configurability is satisfied, process efficiency will be sacrificed. Thus for applications of any significant size, there can be no single hardware or software configuration that can efficiently support all the configurability options of the applications. The Data-Adaptable Reconfigurable Embedded System (DARES) approach tackles this problem through combination of the hardware-software co-design and reconfigurable computing methodologies. Data-adaptability means that as data streams change, the system is reconfigured along the baselines defined within the system’s specifications. In this project we use the concepts of Model-Integrated Computing to implement a domain-specific modeling language for the DARES approach. The language captures all the configurability options of the application task(s), performs design-space exploration, and provides a template for source code generation.

JF - Proceedings of the 8th IEEE Workshop on Model-Based Development for Computer-Based Systems UR - http://dx.doi.org/10.1109/ECBS.2011.31 ER -