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J. Low Power Electron. Appl. 2018, 8(4), 47;

Enabling Energy-Efficient Physical Computing through Analog Abstraction and IP Reuse

Electrical and Computer Engineering (ECE), Georgia Institute of Technology, Atlanta, GA 30332-250, USA
Author to whom correspondence should be addressed.
Received: 1 October 2018 / Revised: 12 November 2018 / Accepted: 16 November 2018 / Published: 24 November 2018
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This paper shows the first step in analog (and mixed signal) abstraction utilized in large-scale Field Programmable Analog Arrays (FPAA), encoded in the open-source SciLab/Xcos based toolset. Having any opportunity of a wide-scale utilization of ultra-low power technology both requires programmability/reconfigurability as well as abstractable tools. Abstraction is essential both make systems rapidly, as well as reduce the barrier for a number of users to use ultra-low power physical computing techniques. Analog devices, circuits, and systems are abstractable and retain their energy efficient opportunities compared with custom digital hardware. We will present the analog (and mixed signal) abstraction developed for the open-source toolkit used for the SoC FPAAs. Abstraction of Blocks in the FPAA block library makes the SoC FPAA ecosystem accessible to system-level designers while still enabling circuit designers the freedom to build at a low level. Multiple working test cases of various levels of complexity illustrate the analog abstraction capability. The FPAA block library provides a starting point for discussing the fundamental block concepts of analog computational approaches. View Full-Text
Keywords: FPAA; Analog Abstraction FPAA; Analog Abstraction

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Hasler, J.; Natarajan, A.; Kim, S. Enabling Energy-Efficient Physical Computing through Analog Abstraction and IP Reuse. J. Low Power Electron. Appl. 2018, 8, 47.

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J. Low Power Electron. Appl. EISSN 2079-9268 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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