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

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.

Analog System High-Level Synthesis for Energy-Efficient Reconfigurable Computing

“…Recent interest in analog tool development follows these directions [21][22][23], building only a few blocks (e.g., current source, differential pair) to make a small analog component (e.g., amplifier, small data converter). A different approach more consistent with digital synthesis for targeting configurable devices and new ICs requires a different approach built upon recent efforts in analog computation abstraction [24]. Recent efforts in FPAAs [4,[25][26][27][28], particularly computational analog blocks (CABs) and CLBs within a dense Manhattan routing fabric (e.g., [4]), created the initial pressure to develop analog synthesis tools [29], building on VPR/VTR [30] to actualize system level designs, leading to recent work in programmable analog standard cells [31].…”

Physical Computing: Unifying Real Number Computation to Enable Energy Efficient Computing

“…Recently, analog computation has developed a framework (Figure 1) that includes analog numerical analysis techniques [16], analog algorithm complexity theory [14], and analog algorithm abstraction theory [17]. Current programmable Analog design is no longer seen as numerically inferior to digital computation [16], or seen as too complex to have levels of abstraction like digital computation [17], or seen to be governed by digital processor techniques where it rather now pushes the questions for both analog and digital architecture questions [14]. Analog computation becomes relevant with the advent of programmable and configurable FPAA devices [18,19] and the associated design and synthesis tools [20,21] incorporating parts of this framework.…”