Buildings are the result of a complex integration of multi-physics subsystems. Besides the obvious civil engineering infrastructure, thermal, electrical, mechanical, control, communication and computing subsystems must co-exist and be operated so that the overall operation is smooth and efficient. This is particularly important for commercial buildings but is also very relevant for residential buildings especially apartment buildings. Unfortunately, the design and deployment of these subsystems is rarely synchronized: lighting, security, heating, ventilation and air conditioning systems are often designed independently. However, simply putting together a collection of sub-systems, albeit optimized, has led to the inefficient buildings of today. Worldwide, buildings consume 42% of all electrical power - more than any other asset - and it can be proven that much of this can be reduced if a holistic approach to design, deployment, and operation is taken. Government agencies, academic institutions, building contractors and owners have realized the significant impact of buildings on the global environment, the electrical grid, and the mission of their organizations. However, the economic impact for all constituencies is still difficult to assess. Government regulations can play a fundamental role, as it has been the case for the transportation industry where regulations on emission and fuel consumption have been the single most important factor of innovation in automotive design. We are convinced that by leveraging technology and utilizing a system-level approach to buildings, they will provide comfort, safety and functionality while minimizing energy cost, supporting a robust electric grid and mitigating environmental impact. Realizing this vision requires adding intelligence from the beginning of the design phase, to deployment, from commissioning to operation, all the way to the end of the building's life cycle. In this issue, we attempt to provide an as-complete-as-possible overview of the activities in the field of smart connected building design automation that attempts to make the vision a reality. The overarching range of such activities includes developing simulation tools for modeling and the design of buildings, and consequently control algorithms proposed to make buildings smarter and more efficient. Furthermore, we will review real-world and large-scale implementation of such control strategies on physical buildings. We then present a formal co-design methodology to design buildings, taking the view that buildings are prime examples of cyber-physical systems where the virtual and physical worlds meet as more traditional products such as thermostats are able to connect online and perform complicated computational tasks to control building temperature effectively. We complete the presentation describing the growing role of buildings in the operation of the smart grid where buildings are not only consumers of energy, but are themselves also
{"title":"Smart Connected Buildings Design Automation: Foundations and Trends","authors":"Mehdi Maasoumy, A. Sangiovanni-Vincentelli","doi":"10.1561/1000000043","DOIUrl":"https://doi.org/10.1561/1000000043","url":null,"abstract":"Buildings are the result of a complex integration of multi-physics subsystems. Besides the obvious civil engineering infrastructure, thermal, electrical, mechanical, control, communication and computing subsystems must co-exist and be operated so that the overall operation is smooth and efficient. This is particularly important for commercial buildings but is also very relevant for residential buildings especially apartment buildings. Unfortunately, the design and deployment of these subsystems is rarely synchronized: lighting, security, heating, ventilation and air conditioning systems are often designed independently. However, simply putting together a collection of sub-systems, albeit optimized, has led to the inefficient buildings of today. Worldwide, buildings consume 42% of all electrical power - more than any other asset - and it can be proven that much of this can be reduced if a holistic approach to design, deployment, and operation is taken. Government agencies, academic institutions, building contractors and owners have realized the significant impact of buildings on the global environment, the electrical grid, and the mission of their organizations. However, the economic impact for all constituencies is still difficult to assess. Government regulations can play a fundamental role, as it has been the case for the transportation industry where regulations on emission and fuel consumption have been the single most important factor of innovation in automotive design. We are convinced that by leveraging technology and utilizing a system-level approach to buildings, they will provide comfort, safety and functionality while minimizing energy cost, supporting a robust electric grid and mitigating environmental impact. Realizing this vision requires adding intelligence from the beginning of the design phase, to deployment, from commissioning to operation, all the way to the end of the building's life cycle. In this issue, we attempt to provide an as-complete-as-possible overview of the activities in the field of smart connected building design automation that attempts to make the vision a reality. The overarching range of such activities includes developing simulation tools for modeling and the design of buildings, and consequently control algorithms proposed to make buildings smarter and more efficient. Furthermore, we will review real-world and large-scale implementation of such control strategies on physical buildings. We then present a formal co-design methodology to design buildings, taking the view that buildings are prime examples of cyber-physical systems where the virtual and physical worlds meet as more traditional products such as thermostats are able to connect online and perform complicated computational tasks to control building temperature effectively. We complete the presentation describing the growing role of buildings in the operation of the smart grid where buildings are not only consumers of energy, but are themselves also ","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78183978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The design of bug-free and safe medical device software is challenging, especially in complex implantable devices. This is due to the device's closed-loop interaction with the patient's organs, which are stochastic physical environments. The life-critical nature and the lack of existing industry standards to enforce software validation make this an ideal domain for exploring design automation challenges for integrated functional and formal modeling with closed-loop analysis. The primary goal of high-confidence medical device software is to guarantee the device will never drive the patient into an unsafe condition even though we do not have complete understanding of the physiological plant. There are two major differences between modeling physiology and modeling man-made systems: first, physiology is much more complex and less well-understood than man-made systems like cars and airplanes, and spans several scales from the molecular to the entire human body. Secondly, the variability between humans is orders of magnitude larger than that between two cars coming off the assembly line. Using the implantable cardiac pacemaker as an example of closed-loop device, and the heart as the organ to be modeled, we present several of the challenges and early results in model-based device validation. We begin with detailed timed automata model of the pacemaker, based on the specifications and algorithm descriptions from Boston Scientific. For closed-loop evaluation, a real-time Virtual Heart Model VHM has been developed to model the electrophysiological operation of the functioning and malfunctioning i.e., during arrhythmia hearts. By extracting the timing properties of the heart and pacemaker device, we present a methodology to construct timed-automata models for formal model checking and functional testing of the closed-loop system. The VHM's capability of generating clinically-relevant response has been validated for a variety of common arrhythmias. Based on a set of requirements, we describe a framework of Abstraction Trees that allows for interactive and physiologically relevant closed-loop model checking and testing for basic pacemaker device operations such as maintaining the heart rate, atrial-ventricle synchrony and complex conditions such as avoiding pacemaker-mediated tachycardia. Through automatic model translation of abstract models to simulation-based testing and code generation for platform-level testing, this model-based design approach ensures the closed-loop safety properties are retained through the design toolchain and facilitates the development of verified software from verified models. This system is a step toward a validation and testing approach for medical cyber-physical systems with the patient-in-the-loop.
{"title":"High-Confidence Medical Device Software Development","authors":"Zhihao Jiang, R. Mangharam","doi":"10.1561/1000000040","DOIUrl":"https://doi.org/10.1561/1000000040","url":null,"abstract":"The design of bug-free and safe medical device software is challenging, especially in complex implantable devices. This is due to the device's closed-loop interaction with the patient's organs, which are stochastic physical environments. The life-critical nature and the lack of existing industry standards to enforce software validation make this an ideal domain for exploring design automation challenges for integrated functional and formal modeling with closed-loop analysis. The primary goal of high-confidence medical device software is to guarantee the device will never drive the patient into an unsafe condition even though we do not have complete understanding of the physiological plant. There are two major differences between modeling physiology and modeling man-made systems: first, physiology is much more complex and less well-understood than man-made systems like cars and airplanes, and spans several scales from the molecular to the entire human body. Secondly, the variability between humans is orders of magnitude larger than that between two cars coming off the assembly line. Using the implantable cardiac pacemaker as an example of closed-loop device, and the heart as the organ to be modeled, we present several of the challenges and early results in model-based device validation. We begin with detailed timed automata model of the pacemaker, based on the specifications and algorithm descriptions from Boston Scientific. For closed-loop evaluation, a real-time Virtual Heart Model VHM has been developed to model the electrophysiological operation of the functioning and malfunctioning i.e., during arrhythmia hearts. By extracting the timing properties of the heart and pacemaker device, we present a methodology to construct timed-automata models for formal model checking and functional testing of the closed-loop system. The VHM's capability of generating clinically-relevant response has been validated for a variety of common arrhythmias. Based on a set of requirements, we describe a framework of Abstraction Trees that allows for interactive and physiologically relevant closed-loop model checking and testing for basic pacemaker device operations such as maintaining the heart rate, atrial-ventricle synchrony and complex conditions such as avoiding pacemaker-mediated tachycardia. Through automatic model translation of abstract models to simulation-based testing and code generation for platform-level testing, this model-based design approach ensures the closed-loop safety properties are retained through the design toolchain and facilitates the development of verified software from verified models. This system is a step toward a validation and testing approach for medical cyber-physical systems with the patient-in-the-loop.","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74007420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Real-time embedded systems have been widely deployed in mission-critical applications, such as avionics mission computing, highway traffic control, remote patient monitoring, wireless communications, navigation, etc. These applications always require their real-time and embedded components to work in open and unpredictable environments, where workload is volatile and unknown. In order to guarantee the temporal correctness and avoid severe underutilization or overload, it is of vital significance to measure, control, and optimize the processor utilization adaptively. A key challenge in this mission is to meet real-time requirements even when the workload cannot be accurately characterized a priori. Traditional approaches of worst-case analysis may cause underutilization of resources, while Model Predictive Control MPC based approaches may suffer severe performance deterioration when large estimation errors exist. To address this challenging problem and provide better system performance, we have developed several important online adaptive optimal control approaches based on advanced control techniques. Our approaches adopt Recursive Least Square RLS based model identification and Linear Quadratic LQ optimal controllers to guarantee that the systems are neither overloaded, nor underloaded. These proposed approaches, as well as the associated tools, can quickly adapt to volatile workload changes to provide stable system performance. To minimize the impact of modeling errors, we adopt the Adaptive Critic Design ACD technique and develop an improved solution that requires little information of the system model. To deal with the discrete task rates, we further propose to utilize the frequency scaling technique to assist the utilization control and optimization. The computational overhead of centralized approaches explodes as the scale of systems increases. To ensure system scalability and global stability, decentralized control and optimization approaches are desired. We leverage an efficient decoupling technique and derive several distributed approaches. These approaches adopt one feedback loop to adjust the task rate, and apply another feedback loop to control the CPU frequency asynchronously. As these two manipulated variables i.e., the CPU frequency and task rate contribute to the system performance together with a strong coupling, asynchronous control approaches may not be able to achieve the optimal performance. To handle this coupling, we further develop a synchronous rate and frequency control and optimization approach. This approach jointly and synchronouslyadjusts rate and frequency settings, and achieves enhanced system performance. All the aforementioned approaches are based on certain mathematical models. However, it is sometimes hard to develop an exact model to characterize a real-time embedded system. In order to deal with this issue, we further develop a model-free utilization control and optimizationsolution by applying the fuzzy logic
{"title":"Utilization Control and Optimization of Real-Time Embedded Systems","authors":"Xue Liu, Xi Chen, Fanxin Kong","doi":"10.1561/1000000042","DOIUrl":"https://doi.org/10.1561/1000000042","url":null,"abstract":"Real-time embedded systems have been widely deployed in mission-critical applications, such as avionics mission computing, highway traffic control, remote patient monitoring, wireless communications, navigation, etc. These applications always require their real-time and embedded components to work in open and unpredictable environments, where workload is volatile and unknown. In order to guarantee the temporal correctness and avoid severe underutilization or overload, it is of vital significance to measure, control, and optimize the processor utilization adaptively. A key challenge in this mission is to meet real-time requirements even when the workload cannot be accurately characterized a priori. Traditional approaches of worst-case analysis may cause underutilization of resources, while Model Predictive Control MPC based approaches may suffer severe performance deterioration when large estimation errors exist. To address this challenging problem and provide better system performance, we have developed several important online adaptive optimal control approaches based on advanced control techniques. Our approaches adopt Recursive Least Square RLS based model identification and Linear Quadratic LQ optimal controllers to guarantee that the systems are neither overloaded, nor underloaded. These proposed approaches, as well as the associated tools, can quickly adapt to volatile workload changes to provide stable system performance. To minimize the impact of modeling errors, we adopt the Adaptive Critic Design ACD technique and develop an improved solution that requires little information of the system model. To deal with the discrete task rates, we further propose to utilize the frequency scaling technique to assist the utilization control and optimization. The computational overhead of centralized approaches explodes as the scale of systems increases. To ensure system scalability and global stability, decentralized control and optimization approaches are desired. We leverage an efficient decoupling technique and derive several distributed approaches. These approaches adopt one feedback loop to adjust the task rate, and apply another feedback loop to control the CPU frequency asynchronously. As these two manipulated variables i.e., the CPU frequency and task rate contribute to the system performance together with a strong coupling, asynchronous control approaches may not be able to achieve the optimal performance. To handle this coupling, we further develop a synchronous rate and frequency control and optimization approach. This approach jointly and synchronouslyadjusts rate and frequency settings, and achieves enhanced system performance. All the aforementioned approaches are based on certain mathematical models. However, it is sometimes hard to develop an exact model to characterize a real-time embedded system. In order to deal with this issue, we further develop a model-free utilization control and optimizationsolution by applying the fuzzy logic","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85732341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing is a new computing paradigm and it is gaining wide popularity due to its benefits including reduced cost, ease of management, and increased reliability. In a cloud computing environment, companies or individuals offload their computing hardware/software/data to the cloud, which is supported by the computing infrastructure called datacenters. Datacenters consume large amounts of electricity to operate and bring enormous electricity bills to the operators. Associated carbon emissions from operating datacenters also cause significant negative impact to the environment. In the mean time, a new kind of electrical grid, called the smart grid, is emerging. Smart grids enable two way communications between the power generators and the power consumers. Smart grid technology brings many salient features to help deliver power efficiently and reliably. There are many research efforts addressing either of the two tracks above. Different with them, we consider both and focus on cost-aware datacenter power management in presence of smart grids. We review recent developments on this area in this article. It involves understanding how a smart grid operates, where power goes in datacenters, and most importantly, how to reduce the power cost and/or negative environmental impact when operating datacenters.
{"title":"Datacenter Power Management in Smart Grids","authors":"Xue Liu, Fanxin Kong","doi":"10.1561/1000000038","DOIUrl":"https://doi.org/10.1561/1000000038","url":null,"abstract":"Cloud computing is a new computing paradigm and it is gaining wide popularity due to its benefits including reduced cost, ease of management, and increased reliability. In a cloud computing environment, companies or individuals offload their computing hardware/software/data to the cloud, which is supported by the computing infrastructure called datacenters. Datacenters consume large amounts of electricity to operate and bring enormous electricity bills to the operators. Associated carbon emissions from operating datacenters also cause significant negative impact to the environment. In the mean time, a new kind of electrical grid, called the smart grid, is emerging. Smart grids enable two way communications between the power generators and the power consumers. Smart grid technology brings many salient features to help deliver power efficiently and reliably. There are many research efforts addressing either of the two tracks above. Different with them, we consider both and focus on cost-aware datacenter power management in presence of smart grids. We review recent developments on this area in this article. It involves understanding how a smart grid operates, where power goes in datacenters, and most importantly, how to reduce the power cost and/or negative environmental impact when operating datacenters.","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82218350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Flexible electronics are emerging as an alternative to conventional Si electronics for large-area low-cost applications such as smart sensors, disposable RFID tags, and solar cells. By utilizing inexpensive manufacturing methods such as ink-jet printing and roll-to-roll imprinting, flexible electronics can be made on low-cost plastic films just like printing newspapers. However, the key elements of flexible electronics, thin-film transistors TFTs, have slower operating speeds and are less reliable than their Si electronics counterparts. Furthermore, depending on the material property, TFTs are usually mono-type - either p- or n-type - devices. Making air-stable complementary TFT circuits is very challenging or not applicable to most TFT technologies. Existing design methodologies for Si electronics, therefore, cannot be directly applied to flexible electronics. Other inhibiting factors such as high supply voltage, large process variation, and lack of trustworthy device modeling also make designing larger-scale and robust TFT circuits a challenge.The objective of this article is to provide an in-depth overview of flexible electronics from their applications, manufacturing processes, device characteristics, to circuit and system design solutions. We first introduce the low-cost fabrication methods for flexible electronics, including ink-jet printing, screen printing, and gravure printing. The device characteristics and compact modeling of four major types of TFT technologies, including hydrogenated amorphous silicon a-Si:H TFT, polymer organic TFT, self-assembly monolayer SAM organic TFT, and metal oxide TFT, will be illustrated. We will then give an overview of digital and analog circuit design from basic logic gates to a microprocessor, as well as design automation tools and methods, for designing flexible electronics. In order to accurately predict the time-dependent degradation of TFT circuits, we describe a reliability simulation framework that can predict the TFT circuits' performance degradation under bias-stress. This framework has been validated using the amorphous-silicon a-Si TFT scan driver for TFT-LCD displays. Finally, we will give an overview of flexible thin-film photovoltaics using different materials including amorphous silicon, CdTe, CIGS , and organic solar cells.
{"title":"Design, Automation, and Test for Low-Power and Reliable Flexible Electronics","authors":"Tsung-Ching Huang, Jiun-Lang Huang, K. Cheng","doi":"10.1561/1000000039","DOIUrl":"https://doi.org/10.1561/1000000039","url":null,"abstract":"Flexible electronics are emerging as an alternative to conventional Si electronics for large-area low-cost applications such as smart sensors, disposable RFID tags, and solar cells. By utilizing inexpensive manufacturing methods such as ink-jet printing and roll-to-roll imprinting, flexible electronics can be made on low-cost plastic films just like printing newspapers. However, the key elements of flexible electronics, thin-film transistors TFTs, have slower operating speeds and are less reliable than their Si electronics counterparts. Furthermore, depending on the material property, TFTs are usually mono-type - either p- or n-type - devices. Making air-stable complementary TFT circuits is very challenging or not applicable to most TFT technologies. Existing design methodologies for Si electronics, therefore, cannot be directly applied to flexible electronics. Other inhibiting factors such as high supply voltage, large process variation, and lack of trustworthy device modeling also make designing larger-scale and robust TFT circuits a challenge.The objective of this article is to provide an in-depth overview of flexible electronics from their applications, manufacturing processes, device characteristics, to circuit and system design solutions. We first introduce the low-cost fabrication methods for flexible electronics, including ink-jet printing, screen printing, and gravure printing. The device characteristics and compact modeling of four major types of TFT technologies, including hydrogenated amorphous silicon a-Si:H TFT, polymer organic TFT, self-assembly monolayer SAM organic TFT, and metal oxide TFT, will be illustrated. We will then give an overview of digital and analog circuit design from basic logic gates to a microprocessor, as well as design automation tools and methods, for designing flexible electronics. In order to accurately predict the time-dependent degradation of TFT circuits, we describe a reliability simulation framework that can predict the TFT circuits' performance degradation under bias-stress. This framework has been validated using the amorphous-silicon a-Si TFT scan driver for TFT-LCD displays. Finally, we will give an overview of flexible thin-film photovoltaics using different materials including amorphous silicon, CdTe, CIGS , and organic solar cells.","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89362686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sudipta Chattopadhyay, Abhik Roychoudhury, Jakob Rosen, P. Eles, Zebo Peng
Multi-core architectures have recently gained popularity due to their high-performance and low-power characteristics. Most of the modern desktop systems are now equipped with multi-core processors. Despite the wide-spread adaptation of multi-core processors in desktop systems, using such processors in embedded systems still poses several challenges. Embedded systems are often constrained by several extra-functional aspects, such as time. Therefore, providing guarantees for time-predictable execution is one of the key requirements for embedded system designers. Multi-core processors adversely affect the time-predictability due to the presence of shared resources, such as shared caches and shared buses. In this contribution, we shall first discuss the challenges imposed by multi-core architectures in designing time-predictable embedded systems. Subsequently, we shall describe, in details, a comprehensive solution to guarantee time-predictable execution on multi-core platforms. Besides, we shall also perform a discussion of different techniques to provide an overview of the state-of-the-art solutions in this topic. Through this work, we aim to provide a solid background on recent trends of research towards achieving time-predictability on multi-cores. Besides, we also highlight the limitations of the state-of-the-art and discuss future research opportunities and challenges to accomplish time-predictable execution on multi-core platforms.
{"title":"Time-Predictable Embedded Software on Multi-Core Platforms: Analysis and Optimization","authors":"Sudipta Chattopadhyay, Abhik Roychoudhury, Jakob Rosen, P. Eles, Zebo Peng","doi":"10.1561/1000000037","DOIUrl":"https://doi.org/10.1561/1000000037","url":null,"abstract":"Multi-core architectures have recently gained popularity due to their high-performance and low-power characteristics. Most of the modern desktop systems are now equipped with multi-core processors. Despite the wide-spread adaptation of multi-core processors in desktop systems, using such processors in embedded systems still poses several challenges. Embedded systems are often constrained by several extra-functional aspects, such as time. Therefore, providing guarantees for time-predictable execution is one of the key requirements for embedded system designers. Multi-core processors adversely affect the time-predictability due to the presence of shared resources, such as shared caches and shared buses. In this contribution, we shall first discuss the challenges imposed by multi-core architectures in designing time-predictable embedded systems. Subsequently, we shall describe, in details, a comprehensive solution to guarantee time-predictable execution on multi-core platforms. Besides, we shall also perform a discussion of different techniques to provide an overview of the state-of-the-art solutions in this topic. Through this work, we aim to provide a solid background on recent trends of research towards achieving time-predictability on multi-cores. Besides, we also highlight the limitations of the state-of-the-art and discuss future research opportunities and challenges to accomplish time-predictable execution on multi-core platforms.","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82754821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vertically-integrated 3D multiprocessors systems-on-chip (3D MPSoCs) provide the means to continue integrating more functionality within a unit area while enhancing manufacturing yields and runtime performance. However, 3D MPSoCs incur amplified thermal challenges that undermine the corresponding reliability. To address these issues, several advanced cooling technologies, alongside temperature-aware design-time optimizations and run-time management schemes have been proposed. In this paper, we provide an overall survey on the recent advances in temperature-aware 3D MPSoC considerations. We explore the recent advanced cooling strategies, thermal modeling frameworks, design-time optimizations and run-time thermal management schemes that are primarily targeted for 3D MPSoCs. Our aim of proposing this survey is to provide a global perspective, highlighting the advancements and drawbacks on the recent state-of-the-art.
{"title":"Temperature-Aware Design and Management for 3D Multi-Core Architectures","authors":"M. Sabry, David Atienza Alonso","doi":"10.1561/1000000032","DOIUrl":"https://doi.org/10.1561/1000000032","url":null,"abstract":"Vertically-integrated 3D multiprocessors systems-on-chip (3D MPSoCs) provide the means to continue integrating more functionality within a unit area while enhancing manufacturing yields and runtime performance. However, 3D MPSoCs incur amplified thermal challenges that undermine the corresponding reliability. To address these issues, several advanced cooling technologies, alongside temperature-aware design-time optimizations and run-time management schemes have been proposed. In this paper, we provide an overall survey on the recent advances in temperature-aware 3D MPSoC considerations. We explore the recent advanced cooling strategies, thermal modeling frameworks, design-time optimizations and run-time thermal management schemes that are primarily targeted for 3D MPSoCs. Our aim of proposing this survey is to provide a global perspective, highlighting the advancements and drawbacks on the recent state-of-the-art.","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91345647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Providing a constant and perpetual energy source is a key design challenge for implantable medical devices. Harvesting energy from the human body and the surrounding is one of the possible solutions. Delivering energy from outside the body through different wireless media is another feasible solution. In this monograph, we review different state-of-the-art mechanisms that do "in-body" energy harvesting as well as "out-of-body" wireless power delivery. Details of the energy sources, transmission media, energy harvesting and coupling techniques, and the required energy transducers will be discussed. The merits and disadvantages of each approach will be presented. Different mechanisms have very different characteristics on their output voltage, amount of harvested power and power transfer efficiency. Therefore different types of power conditioning circuits are required. Issues of designing the building blocks for the power conditioning circuits for different energy harvesting or coupling mechanisms will be compared.
{"title":"Energy Harvesting and Power Delivery for Implantable Medical Devices","authors":"C. Tsui, Xing Li, W. Ki","doi":"10.1561/1000000029","DOIUrl":"https://doi.org/10.1561/1000000029","url":null,"abstract":"Providing a constant and perpetual energy source is a key design challenge for implantable medical devices. Harvesting energy from the human body and the surrounding is one of the possible solutions. Delivering energy from outside the body through different wireless media is another feasible solution. In this monograph, we review different state-of-the-art mechanisms that do \"in-body\" energy harvesting as well as \"out-of-body\" wireless power delivery. Details of the energy sources, transmission media, energy harvesting and coupling techniques, and the required energy transducers will be discussed. The merits and disadvantages of each approach will be presented. Different mechanisms have very different characteristics on their output voltage, amount of harvested power and power transfer efficiency. Therefore different types of power conditioning circuits are required. Issues of designing the building blocks for the power conditioning circuits for different energy harvesting or coupling mechanisms will be compared.","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87123547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Technology scaling has resulted in an increasing magnitude of and sensitivity to manufacturing process variations. This has led to the adoption of statistical design methodologies as opposed to conventional static design techniques. At the same time, increasing design complexity has motivated a shift toward higher levels of design abstraction, i.e., micro-architecture and system level design. In this survey, we highlight emerging statistical design techniques targeted toward the analysis and mitigation of process variation at the system level design abstraction, for both conventional planar and emerging 3D integrated circuits. The topics covered include variability macro-modeling for logic modules, system level variability analysis for multi-core systems, and system level variability mitigation techniques. We conclude with some pointers toward future research directions.
{"title":"Addressing Process Variations at the Microarchitecture and System Level","authors":"S. Garg, Diana Marculescu","doi":"10.1561/1000000031","DOIUrl":"https://doi.org/10.1561/1000000031","url":null,"abstract":"Technology scaling has resulted in an increasing magnitude of and sensitivity to manufacturing process variations. This has led to the adoption of statistical design methodologies as opposed to conventional static design techniques. At the same time, increasing design complexity has motivated a shift toward higher levels of design abstraction, i.e., micro-architecture and system level design. In this survey, we highlight emerging statistical design techniques targeted toward the analysis and mitigation of process variation at the system level design abstraction, for both conventional planar and emerging 3D integrated circuits. The topics covered include variability macro-modeling for logic modules, system level variability analysis for multi-core systems, and system level variability mitigation techniques. We conclude with some pointers toward future research directions.","PeriodicalId":42137,"journal":{"name":"Foundations and Trends in Electronic Design Automation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87369547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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