This paper presents an internally compensated two stage operational amplifier fabricated using unipolar a-IGZO TFT devices integrated on flexible polyimide substrate. A new active load configuration is introduced to realize high incremental impedance and serve as the stage load of the amplifier. The opamp has been manufactured and measured to have 57 dB of open-loop DC-gain and a unity gain frequency of 311 kHz. Further, the internal compensation sets the dominant pole of the opamp achieving a phase margin of 75 degrees. A common mode feedback scheme has been implemented to bias the fully differential gain stages using an auxiliary two-stage OpAmp realized with a conventional diode-connected transistor stage load. This design, to our knowledge, surpasses the highest reported performance of (operational) amplifiers made in a-IGZO technology.
To enable energy-efficient embedded execution of Deep Neural Networks (DNNs), the critical sections of these workloads, their multiply-accumulate (MAC) operations, need to be carefully optimized. The SotA pursues this through runtime precision-scalable MAC operators, which can support the varying precision needs of DNNs in an energy-efficient way. Yet, to implement the adaptable precision MAC operation, most SotA solutions rely on separately optimized low precision multipliers and a precision-variable accumulation scheme, with the possible disadvantages of a high control complexity and degraded throughput. This paper, first optimizes one of the most effective SotA techniques to support fully-connected DNN layers. This mode, exploiting the transformation of a high precision multiplier into independent parallel low-precision multipliers, will be called the Sum Separate (SS) mode. In addition, this work suggests an alternative low-precision scheme, i.e. the implicit accumulation of multiple low precision products within the multiplier itself, called the Sum Together (ST) mode. Based on the two types of MAC arrangements explored, corresponding architectures have been proposed to implement DNN processing. The two architectures, yielding the same throughput, are compared in different working precisions (2/4/8/16-bit), based on Post-Synthesis simulation. The result shows that the proposed ST-Mode based architecture outperforms the earlier SS-Mode by up to ×1.6 on Energy Efficiency (TOPS/W) and ×1.5 on Area Efficiency (GOPS/mm 2 ).
This letter presents analysis of an inherently stable positive-feedback based active load, first reported in our prior work, to realize high gain analog amplifiers using unipolar a-IGZO TFT technology. Additionally reported are theoretical performance bounds and design guidelines to maximally utilize a general positive-feedback scheme for the active load while maintaining stability. To demonstrate a design implementation, a single stage fully differential operational transconductance amplifier with common mode feedback has been manufactured and measured to have 40 dB open-loop gain at DC and a unity gain frequency of 61 kHz while driving a 30 pF load capacitance.
This paper presents the design of a readout circuit for charge-output sensor arrays integrated on flexible substrate. The Charge-Integrating-Amplifier is built with a current-output transimpedance amplifier that includes integrator function with reset. The Charge-Integrating-Amplifier has a fully differential internal topology, improving over single ended design, including the feedback amplifier implemented specifically as a Nauta-transconductor. The readout circuit has been manufactured in a 3µm LTPS process on foil and measured, achieving a bandwidth of 200kHz, operation at a 5V supply while consuming 586µW power and maintaining a maximum INL of 5%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.