Abstract
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.
Highlights
Developing abstraction of analog is considered an unlikely dream, this paper shows the first step in analog abstraction utilized in large-scale Field Programmable Analog Arrays (FPAA), encoded in the open-source SciLab/Xcos based toolset (Figure 1)
Six to either abstraction levels, typical of digital computation, are common for implementing this level of computation. These systems allow for sensors to classified symbolic data, a significant challenge for any system and interface design utilizing popular neural network accelerator hardware solutions
We see the first step in analog abstraction utilized in FPAA, encoded in the open-source SciLab/Xcos based toolset
Summary
Developing abstraction of analog is considered an unlikely dream, 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 (Figure 1). Analog abstraction will focus on algorithmic abstraction, such as filtering, subband processing, and classification, as the analog equivalent of multiply and addition tend to be circuits requiring one (or a few) transistors per input vector component [9]. These presented techniques are only the beginning of these directions. Reviewing the SoC FPAA ecosystem and energy efficiency discussions (Section 2) provides the background for developing abstraction This background enables developing design approaches for abstraction and resulting library blocks (Section 3). We conclude by discussing the FPAA block library (Section 6), discussing the implications for the existing library as well as speculation on fundamental block concepts of analog computational approaches
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