Compute in-memory (CIM) is an exciting technique that minimizes data transport, maximizes memory throughput, and performs computation on the bitline of memory sub-arrays. This is especially interesting for machine learning applications, where increased memory bandwidth and analog domain computation offer improved area and energy efficiency. Unfortunately, CIM faces new challenges traditional CMOS architectures have avoided. In this work, we explore the impact of device variation (calibrated with measured data on foundry RRAM arrays) and propose a new class of error correcting codes (ECC) for hard and soft errors in CIM. We demonstrate single, double, and triple error correction offering over 16,000× reduction in bit error rate over a design without ECC and over 427× over prior work, while consuming only 29.1% area and 26.3% power overhead.

This paper presents a simulation-based study to evaluate the effect of Hot Carrier Injection (HCI) on the characteristics of an on-chip, digitally-controlled, switched inductor voltage regulator (IVR) architecture. Our methodology integrates device-level aging models, circuit simulations in SPICE, and control loop simulations in Simulink. We characterize the effect of HCI on individual components of an IVR, and their combined effect on the efficiency and transient performance. Our analysis using an IVR designed in 65nm CMOS shows that aging of the power stages has a smaller impact on performance compared to that of the control loop. Further, we perform a comparative analysis to show that, with a 1.8V supply, HCI leads to higher aging-induced degradation of IVR than Negative Bias Temperature Instability (NBTI). Finally, our simulation shows that parasitic inductance near IVR input aggravates NBTI and parasitic capacitance near IVR output aggravates HCI effects on IVR’s performance.

Accurate characterization of radiation-induced soft errors is a critical step toward understanding the impact of these glitches on circuit and system reliability. With process scaling, there has been exponential increase in number of transistors that can be packed on a die which, in turn, results in higher sensitive node count and persistent soft error susceptibilities. In this work, a novel circuit technique employing higher sensitivity toward soft errors is proposed. The circuit makes use of current-starved gates with bias knobs to fine-tune both measurement resolution and strike sensitivity enabling accelerated and efficient induction of errors in a limited-time irradiation test environment. The back-sampling chain (BSC) circuit can measure individual radiation-induced transient pulse with as low amplitude as$0.3\times $VDD while maintaining a high measurement resolution for pulsewidth characterization. The bias knobs allowing tuning of sensitivity and resolution enable, for the first time, a strike pulse waveform reconstruction methodology that can be used to calibrate current pulse models for assessing soft error rate (SER) sensitivity of standard logic gates.

This session brings together specialists from the DfT, DfY and DfR domains that will address key problems together with their solutions for the 14 nm node and beyond, dealing with extremely complex chips affected by high defect levels, unpredictable and heterogeneous timing behavior, circuit degradation over time, including extreme situations related with the ultimate CMOS nodes, where all processor nodes, routers and links of single-chip massively parallel tera-device processors could comprise timing faults (such as delay faults or clock skews); a large percentage of these parts are affected by catastrophic failures; all parts experience significant performance degradations over time; and new catastrophic failures occur at low MTBF.

Traditional processors are designed to guarantee error-free operation under worst-case (1) device & interconnect parameter variations resulting from less than ideal manufacturing process control; (2) static & erratic defects; (3) operating environments such as temperature excursions and voltage droops; (4) critical path activation and path delay degradations due to multiple inputs switching simultaneously in gates containing transistor stacks, or signal coupling from neighboring lines in interconnect paths; (5) speed degradation over the operating lifetime due to transistor aging under voltage, temperature & current stress; (6) early-life failures due to latent defect accelerations; and (7) soft error due to cosmic rays and alpha particle impacts. The voltage-frequency settings for all processors are set based on these infrequently encountered worst-case considerations, even though under typical conditions voltage can be pushed down further or frequency increased without causing errors for most of the processors, thus limiting both energy efficiency and performance in scaled CMOS technologies.

Conventional microprocessors require a clock frequency (F CLK ) guardband to ensure correct functionality during infrequent dynamic operating variations in supply voltage (V CC ), temperature, and transistor aging. Consequently, these inflexible designs cannot exploit opportunities for higher performance by increasing F CLK or lower energy by reducing V CC during favorable operating conditions. This presentation describes a 45nm resilient microprocessor with error-detection and recovery circuits to detect and correct timing errors from dynamic variations to mitigate the F CLK guardband, thus enabling higher performance or lower energy as compared to a conventional design. The microprocessor core supports two distinct error-detection designs and two separate error-recovery techniques, allowing a direct comparison of the relative trade-offs. Silicon measurements demonstrate that resilient circuits enable a 41% throughput gain at equal energy or a 22% energy reduction at equal throughput, as compared to a conventional design when executing a benchmark program with a 10% V CC droop. In addition, the resilient circuits guide an adaptive clock controller that tracks recovery cycles and adapts to persistent variations by changing F CLK . The combination of error-detection and recovery circuits with dynamic adaptation allows the microprocessor to adapt to the operating environment to deliver maximum efficiency. The presentation concludes by discussing the opportunity of applying resilient techniques to enhance the dynamic operating range (i.e., high-performance and low-power modes) for microprocessors.

Ubiquitous computing has a number of compelling applications ranging from biomedical sensing to environmental monitoring. These computing systems require low cost sensor nodes with volumes ≪1mm3and lifetimes on the order of months or years. We advocate the use of aggressively scaled supply voltages in such applications to maximize energy efficiency. This paper reviews our recent progress in mapping out the low energy design space. We explore the design and test of three low voltage systems targeting ubiquitous computing. We conclude with a survey of open research directions in the ultra-low energy design space.