AMALGHMA -An environment for measuring execution time and energy consumption in embedded systems

Silva, B.; Tavares, Eduardo; Maciel, Paulo; Nogueira, Bruno; Oliveira, Joao Paulo Nogueira de; Dâmaso, Antônio; Rosa, Nelson Souto

doi:10.1109/smc.2014.6974447

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…One major drawback of a hardware-based energy measurement scheme is that it mandates a periodic measurement of energy expenditure which require support of additional hardware based measuring tools, such as Advanced Measurement Algorithms for Hardware Architectures (AMALGHMA) in conjunction with an oscilloscope and a micrometers [38], [39]. So, this scheme is not cost effective in the long run for sensor networks that are large and densely deployed.…”

Section: Energy Management Schemes a A Life-cycle Modelmentioning

confidence: 99%

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

et al. 2021

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Section: Energy Management Schemes a A Life-cycle Modelmentioning

confidence: 99%

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

et al. 2021

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“…There is previous work that attempt to recognize programming events by means of border detection algorithms. This is, for instance, the approach of Silva et al [Silva et al (2014)], or Nazare et al [Nazaré et al (2014)]. The idea is simple: if we assume that the hardware consumes more energy when it runs a program, then we can expect an isolated, flat-topped hill on its energy skyline.…”

Section: Related Workmentioning

confidence: 99%

JetsonLEAP: A framework to measure power on a heterogeneous system-on-a-chip device

Bessa

Gull

Quintão

et al. 2019

Science of Computer Programming

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Computer science marches towards energy-aware practices. This trend impacts not only the design of computer architectures, but also the design of programs. However, developers still lack affordable and accurate technology to measure energy consumption in computing systems. The goal of this paper is to mitigate such problem. To this end, we introduce JetsonLEAP, a framework that supports the implementation of energy-aware programs. Jet-sonLEAP consists of an embedded hardware, in our case, the Nvidia Tegra TK1 System-on-a-chip device, a circuit to control the flow of energy, of our own design, plus a library to instrument program parts. We discuss two different circuit setups. The most precise setup lets us reliably measure the energy spent by 225,000 instructions, the least precise, although more affordable setup, gives us a window of 975,000 instructions. To probe the precision of our system, we use it in tandem with a high-precision, high-cost acquisition system, and show that results do not differ in any significant way from those that we get using our simpler apparatus. Our entire infrastructure -board, power meter and both circuits -can be reproduced with about $500.00. To demonstrate the efficacy of our framework, we have used it to measure the energy consumed by programs running on ARM cores, on the GPU, and on a remote server. Furthermore, we have studied the impact of OpenACC directives on the energy efficiency of high-performance applications.

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“…In order to perform the experiments and to efficiently measure the power consumption of a WSN node, the AMALGHMA (advanced measurement algorithms for hardware architecture) [ 36 , 37 ] receives the captured information as an input for calculating the power consumption.…”

Section: Experimental Evaluationmentioning

confidence: 99%

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

Bispo

Rosa

Cunha

2015

Sensors

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Wireless sensor networks (WSNs) are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to maximize its lifetime. In this context, this paper presents SITRUS (semantic infrastructure for wireless sensor networks), which aims to reduce the power consumption of WSN nodes using ontologies. SITRUS consists of two major parts: a message-oriented middleware responsible for both an oriented message communication service and a reconfiguration service; and a semantic information processing module whose purpose is to generate a semantic database that provides the basis to decide whether a WSN node needs to be reconfigurated or not. In order to evaluate the proposed solution, we carried out an experimental evaluation to assess the power consumption and memory usage of WSN applications built atop SITRUS.

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AMALGHMA -An environment for measuring execution time and energy consumption in embedded systems

Cited by 6 publications

References 18 publications

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

JetsonLEAP: A framework to measure power on a heterogeneous system-on-a-chip device

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

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