A Non-Stop Double Buffering Mechanism for Dataflow Architecture

Xu, Tianheng; Shen, Xiaowei; Ye, Xiaochun; Da, Wang; Fan, Dongrui; Zhang, Lunkai; Li, Wenming; Zhang, Zhimin; Tang, Zhimin

doi:10.1007/s11390-017-1747-6

Cited by 12 publications

(3 citation statements)

References 25 publications

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“…In addition, there are multiple applications used in other disciplines that help doublebuffering techniques to take samples (or transfer them between memories) while the data are processed in the same processor as Tan et al [35] suggest. This double-buffering technique has been used in image processing [41], paralleling processing [25] or ultrasound imaging methods [4].…”

Section: Data Acquisition Processesmentioning

confidence: 99%

Continuous energy consumption measure approach using a DMA double-buffering technique

Vaquerizo-Hdez

Muñoz

Barrero

et al. 2021

J Wireless Com Network

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Measuring the consumption of electronic devices is a difficult and sensitive task. Data acquisition (DAQ) systems are often used to determine such consumption. In theory, measuring energy consumption is straight forward, just by acquiring current and voltage signals we can determine the consumption. However, a number of issues arise when a fine analysis is required. The main problem is that sampling frequencies have to be high enough to detect variations in the assessed signals over time. In that regard, some popular DAQ systems are based on RISC ARM processors for microcontrollers combined with analog-to-digital converters to meet high-frequency acquisition requirements. The efficient use of direct memory access (DMA) modules combined with pipelined processing in a microcontroller allows to improve the sample rate overcoming the processing time and the internal communication protocol limitations. This paper presents a novel approach for high-frequency energy measurement composed of a DMA rate improvement (data acquisition logic), a data processing logic and a low-cost hardware. The contribution of the paper is the combination of a double-buffered signal acquisition mechanism and an algorithm that computes the device’s energy consumption using parallel data processing. The combination of these elements enables a high-frequency (continuous) energy consumption measurement of an electronic device, improving the accuracy and reducing the cost of existing systems. We have validated our approach by measuring the energy consumed by elemental circuits and wireless sensors networks (WSNs) motes. The results indicate that the energy measurement error is less than 5% and that the proposed method is suitable to measure WSN motes even during sleep cycles, enabling a better characterization of their consumption profile.

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Section: Data Acquisition Processesmentioning

confidence: 99%

Continuous energy consumption measure approach using a DMA double-buffering technique

Vaquerizo-Hdez

Muñoz

Barrero

et al. 2021

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…In addition, there are multiple applications used in other disciplines that help double-buffering techniques to take samples (or transfer them between memories) while the data are processed in the same processor as Tan et al [33] suggest. This double-buffering technique has been used in image processing [39], paralleling processing [25] or ultrasound imaging methods [4].…”

Section: Data Acquisition Processesmentioning

confidence: 99%

Continuously Energy Consumption Measure Approach Using a DMA Double-Buffering Technique

Hernández

Muñoz

Barrero

et al. 2020

Preprint

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Measuring the consumption of electronic devices is a difficult and sensitive task. Data AcQuisition (DAQ) systems are often used to determine such consumption. In theory, measuring energy consumption is straightforward, just by acquiring current and voltage signals we can determine the consumption. However, a number of issues arise when a ne analysis is required. The main problem is that sampling frequencies have to be high enough to detect variations in the assessed signals over time. In that regard, some popular DAQ systems are based on RISC ARM processors for microcontrollers combined with Analog-Digital Converters (ADC) to meet the frequency acquisition requirements. The efficient use of the Direct Memory Access (DMA) modules combined with pipelined processing in the microcontroller allows to improve the sample rate overcoming the processing time and the internal communication protocol limitations. This paper presents a novel approach for high frequency energy measurement composed of a DMA rate improvement (data acquisition logic), a data processing logic and a low-cost hardware. The contribution of the paper is the combination of a double buffered signal acquisition mechanism and an algorithm that computes the device's energy consumption using parallel data processing. The combination of these elements enables a high-frequency (continuous) energy consumption measurement of an electronic device, improving the accuracy and reducing the cost of existing systems. We have validated our approach by measuring the energy consumed by basic circuits and Wireless Sensors Networks (WSNs) motes. The results indicate that the energy measurement error is less than 5%, and that the proposed method is suitable to measure WSN motes even during sleep cycles, enabling a better characterization of their consumption prole.

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“…It was also found that using p=1, and thus only using the relay node without sending data directly to the sink node resulted in a suboptimal solution. The authors of [29] use two buffers to hide the latency of data transfers between on chip and off chip memory for dataflow architectures. The dataflow architecture is very useful for ingesting data, an architecture that is prominently used by Google in its "Dataflow" serverless cloud service [6].…”

Section: Current Uses Of Buffers For Communicationmentioning

confidence: 99%

Methods and Techniques for Inter-cloud Data Transfers

Contreras¹

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This thesis focuses on methods and techniques for transferring data from a compute cloud to a storage cloud by using a buffer at the compute cloud. A space driven, a time driven, and a hybrid buffering technique are discussed. It was found that using buffering at the compute cloud is only beneficial when the load on the system is high. To improve performance a threshold-based and a machine learning based adaptive method are introduced at the buffer to dynamically change between buffering techniques at runtime based on the load on the system state. Using the adaptive methods leads to a significant improvement in performance. A proof-of-concept prototype was built for the different data transfer methods and techniques researched. Experiments performed on the prototype provide insights into system behaviour and performance.

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A Non-Stop Double Buffering Mechanism for Dataflow Architecture

Cited by 12 publications

References 25 publications

Continuous energy consumption measure approach using a DMA double-buffering technique

Continuous energy consumption measure approach using a DMA double-buffering technique

Continuously Energy Consumption Measure Approach Using a DMA Double-Buffering Technique

Methods and Techniques for Inter-cloud Data Transfers

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