We present FlexiFlow, a lifetime-aware design framework for item-level intelligence (ILI) where computation is integrated directly into disposable products like food packaging and medical patches. Our framework leverages natively flexible electronics which offer significantly lower costs than silicon but are limited to kHz speeds and several thousands of gates. Our insight is that unlike traditional computing with more uniform deployment patterns, ILI applications exhibit 1000× variation in operational lifetime, fundamentally changing optimal architectural design decisions when considering trillion-item deployment scales. To enable holistic design and optimization, we model the trade-offs between embodied carbon footprint and operational carbon footprint based on application-specific lifetimes. The framework includes: (1) FlexiBench, a workload suite targeting sustainability applications from spoilage detection to health monitoring; (2) FlexiBits, area-optimized RISC-V cores with 1/4/8-bit datapaths achieving 2.65× to 3.50× better energy efficiency per workload execution; and (3) a carbon-aware model that selects optimal architectures based on deployment characteristics. We show that lifetime-aware microarchitectural design can reduce carbon footprint by 1.62×, while algorithmic decisions can reduce carbon footprint by 14.5×. We validate our approach through the first tape-out using a PDK for flexible electronics with fully open-source tools, achieving 30.9\,kHz operation. FlexiFlow enables exploration of computing at the Extreme Edge where conventional design methodologies must be reevaluated to account for new constraints and considerations. FlexiFlow is available at https://github.com/harvard-edge/FlexiFlow.

Many emerging flexible electronics [1] applications require hardware-based encryption, but it is unclear if practical hardware-based encryption is possible for flexible applications due to stringent power requirements of these applications and high area and power overheads of flexible technologies relative to silicon CMOS technologies. In this work, we observe that the lifetime of many flexible applications is so small that often one key suffices for the entire lifetime. This means that, instead of generating keys and round keys in hardware, we can generate the round keys offline, and instead store these round keys directly on the engine post fabrication in an on-chip programmable read-only memory. This eliminates the need for hardware for dynamic generation of round keys, which significantly reduces encryption overhead, while still allowing engines to have unique keys. This significant reduction in encryption overhead allows us to demonstrate the first practical flexible encryption engines. To prevent an adversary from reading out the stored round keys, we scramble the round keys before storing them in the ROM; camouflage cells are used to unscramble the keys before feeding them to logic. In spite of the unscrambling overhead, our encryption engines consume 27.4% lower power than the already heavily area and power-optimized baselines, while being 21.9% smaller on average.

Flexible electronics is a promising approach to target applications whose computational needs are not met by traditional silicon-based electronics due to their conformality, thinness, or cost requirements. A microprocessor is a critical component for many such applications; however, it is unclear whether it is feasible to build flexible processors at scale (i.e., at high yield), since very few flexible microprocessors have been reported and no yield data or data from multiple chips has been reported. Also, prior manufactured flexible systems were not field-reprogrammable and were evaluated either on a simple set of test vectors or a single program. A working flexible microprocessor chip supporting complex or multiple applications has not been demonstrated. Finally, no prior work performs a design space of flexible microprocessors to optimize area, code size, and energy of such microprocessors.

Among the time-frequency distributions, the Wigner distribution (WD) is found to be one of the most powerful tools for time-frequency analysis. We have therefore developed an interactive simulator for time-frequency analysis based on a discrete version of the WD. The WD behavior is then studied for any frequency modulated and time limited signal. The properties of the WD make possible the detection of time-varying signals in the time-frequency domain. An application is presented where the problem is to automatically detect moving bubbles formed in the human blood under hyperbaric environments. We show that time-frequency analysis by means of the WD is an appropriate method to discriminate the bubble signals from the noise. We present some of our results.