Energy Transparency for Deeply Embedded Programs

Georgiou, Kyriakos; Kerrison, Steve; Chamski, Zbigniew; Eder, Kerstin

doi:10.1145/3046679

Cited by 24 publications

(22 citation statements)

References 52 publications

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“…The technique has been used for static energy consumption analysis at the LLVM IR level in Refs. [14,15] and also in Ref. [16].…”

Section: Energy Modelling At Higher Levels Of Software Abstractionmentioning

confidence: 74%

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Energy-Aware Software Engineering

Eder¹,

Gallagher

2017

ICT - Energy Concepts for Energy Efficiency and Sustainability

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A great deal of energy in Information and Communication Technology (ICT) systems can be wasted by software, regardless of how energy-efficient the underlying hardware is. To avoid such waste, programmers need to understand the energy consumption of programs during the development process rather than waiting to measure energy after deployment. Such understanding is hindered by the large conceptual gap from hardware, where energy is consumed, to high-level languages and programming abstractions. The approaches described in this chapter involve two main topics: energy modelling and energy analysis. The purpose of modelling is to attribute energy values to programming constructs, whether at the level of machine instructions, intermediate code or source code. Energy analysis involves inferring the energy consumption of a program from the program semantics along with an energy model. Finally, the chapter discusses how energy analysis and modelling techniques can be incorporated in software engineering tools, including existing compilers, to assist the energy-aware programmer to optimise the energy consumption of code.

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“…The technique has been used for static energy consumption analysis at the LLVM IR level in Refs. [14,15] and also in Ref. [16].…”

Section: Energy Modelling At Higher Levels Of Software Abstractionmentioning

confidence: 74%

“…[14]. The energy characteristics of LLVM IR instructions are determined from the costs of the associated machine instructions based on a mapping that tracks which LLVM IR instructions created which machine instructions during the lowering phase of compilation, i.e.…”

Section: Energy Modelling At Higher Levels Of Software Abstractionmentioning

confidence: 99%

Energy-Aware Software Engineering

Eder¹,

Gallagher

2017

ICT - Energy Concepts for Energy Efficiency and Sustainability

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“…Recent work [5] demonstrated a new profiling technique that collects execution statistics at the compiler's IR level. This was combined with a dynamic mapping technique that lifts an ISA energy model to the compiler's IR, to retrieve energy estimations at the IR level.…”

Section: Profiling-based Energy Consumption Estimationmentioning

confidence: 99%

“…In [10], the technique was used to extract energy consumption bounds on a simulated processor. More recently [5], IPET was applied at the ISA level of a multi-threaded/core embedded architecture, using an ISA energy model, and at the compiler's IR level, using a mapping technique that lifts ISA energy models to the compiler's IR level. The authors also demonstrated how the technique can be used for design space exploration for two concurrency patterns: task-farms and pipelined programs.…”

Section: Sra-based Energy Consumption Estimationmentioning

confidence: 99%

The IoT Energy Challenge: A Software Perspective

Georgiou

Xavier‐de‐Souza

Eder

2018

IEEE Embedded Syst. Lett.

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Abstract. The Internet of Things (IoT) sparks a whole new world of embedded applications. Most of these applications are based on deeply embedded systems that have to operate on limited or unreliable sources of energy, such as batteries or energy harvesters. Meeting the energy requirements for such applications is a hard challenge, which threatens the future growth of the IoT. Software has the ultimate control over hardware. Therefore, its role is significant in optimizing the energy consumption of a system. Currently, programmers have no feedback on how their software affects the energy consumption of a system. Such feedback can be enabled by energy transparency, a concept that makes a program's energy consumption visible, from hardware to software. This paper discusses the need for energy transparency in software development and emphasizes on how such transparency can be realized to help tackling the IoT energy challenge.

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“…The Ciao pre-processor can then bound the power consumption as a function of input data sizes. This technique was later extended to use a power model at the level of the compiler's intermediate representation rather than the ISA level [67]. This approach applies to programs that can be translated into a logic program.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Decision Policies With Predictable Performance

et al. 2018

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As methods and tools for Cyber-Physical Systems grow in capabilities and use, one-size-fits-all solutions start to show their limitations. In particular, tools and languages for programming an algorithm or modeling a CPS that are specific to the application domain are typically more usable, and yield better performance, than general-purpose languages and tools. In the domain of cardiac arrhythmia monitoring, a small, implantable medical device continuously monitors the patient's cardiac rhythm and delivers electrical therapy when needed. The algorithms executed by these devices are streaming algorithms, so they are best programmed in a streaming language that allows the programmer to reason about the incoming data stream as the basic object, rather than force her to think about lower-level details like state maintenance and minimization. Because these devices are resource-constrained, it is useful if the programming language allowed predictable performance in terms of processing runtime and energy consumption, or more general costs. StreamQRE is a declarative streaming programming language, with an efficient and portable implementation and strong theoretical guarantees. In particular, its evaluation algorithm guarantees constant cost (runtime, memory, energy) per data item, and also calculates upper bounds on the per-item cost. Such an estimate of the cost allows early exploration of the algorithmic possibilities, while maintaining a handle on worst-case performance, on the basis of which hardware can be designed and algorithms can be tuned. Abstract-As methods and tools for Cyber-Physical Systems grow in capabilities and use, one-size-fits-all solutions start to show their limitations. In particular, tools and languages for programming an algorithm or modeling a CPS that are specific to the application domain are typically more usable, and yield better performance, than general-purpose languages and tools. In the domain of cardiac arrhythmia monitoring, a small, implantable medical device continuously monitors the patient's cardiac rhythm and delivers electrical therapy when needed. The algorithms executed by these devices are streaming algorithms, so they are best programmed in a streaming language that allows the programmer to reason about the incoming data stream as the basic object, rather than force her to think about lower-level details like state maintenance and minimization. Because these devices are resource-constrained, it is useful if the programming language allowed predictable performance in terms of processing runtime and energy consumption, or more general costs. StreamQRE is a declarative streaming programming language, with an efficient and portable implementation and strong theoretical guarantees. In particular, its evaluation algorithm guarantees constant cost (runtime, memory, energy) per data item, and also calculates upper bounds on the per-item cost. Such an estimate of the cost allows early exploration of the algorithmic possibilities, while maintaining a handle on worst-case per...

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Energy Transparency for Deeply Embedded Programs

Cited by 24 publications

References 52 publications

Energy-Aware Software Engineering

Energy-Aware Software Engineering

The IoT Energy Challenge: A Software Perspective

Real-Time Decision Policies With Predictable Performance

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