Benton H. Calhoun

Modeling and sizing for minimum energy operation in subthreshold circuits

This paper examines energy minimization for circuits operating in the subthreshold region. Subthreshold operation is emerging as an energy-saving approach to many energy-constrained applications where processor speed is less important. In this paper, we solve equations for total energy to provide an analytical solution for the optimum V/sub DD/ and V/sub T/ to minimize energy for a given frequency in subthreshold operation. We show the dependence of the optimum V/sub DD/ for a given technology on design characteristics and operating conditions. This paper also examines the effect of sizing on energy consumption for subthreshold circuits. We show that minimum sized devices are theoretically optimal for reducing energy. A fabricated 0.18-/spl mu/m test chip is used to compare normal sizing and sizing to minimize operational V/sub DD/ and to verify the energy models. Measurements show that existing standard cell libraries offer a good solution for minimizing energy in subthreshold circuits.

Body Area Sensor Networks: Challenges and Opportunities

Body area sensors can enable novel applications in and beyond healthcare, but research must address obstacles such as size, cost, compatibility, and perceived value before networks that use such sensors can become widespread.

A 256-kb 65-nm Sub-threshold SRAM Design for Ultra-Low-Voltage Operation

Low-voltage operation for memories is attractive because of lower leakage power and active energy, but the challenges of SRAM design tend to increase at lower voltage. This paper explores the limits of low-voltage operation for traditional six-transistor (6T) SRAM and proposes an alternative bitcell that functions too much lower voltages. Measurements confirm that a 256-kb 65-nm SRAM test chip using the proposed bitcell operates into sub-threshold to below 400 mV. At this low voltage, the memory offers substantial power and energy savings at the cost of speed, making it well-suited to energy-constrained applications. The paper provides measured data and analysis on the limiting effects for voltage scaling for the test chip.

Design considerations for ultra-low energy wireless microsensor nodes

This tutorial paper examines architectural and circuit design techniques for a microsensor node operating at power levels low enough to enable the use of an energy harvesting source. These requirements place demands on all levels of the design. We propose architecture for achieving the required ultra-low energy operation and discuss the circuit techniques necessary to implement the system. Dedicated hardware implementations improve the efficiency for specific functionality, and modular partitioning permits fine-grained optimization and power-gating. We describe modeling and operating at the minimum energy point in the subthreshold region for digital circuits. We also examine approaches for improving the energy efficiency of analog components like the transmitter and the ADC. A microsensor node using the techniques we describe can function in an energy-harvesting scenario.

Ultra-dynamic Voltage scaling (UDVS) using sub-threshold operation and local Voltage dithering

Local voltage dithering provides near optimum savings when workload varies for fine-grained blocks. Combining this approach with sub-threshold operation permits ultra-dynamic voltage scaling from 1.1 V to below 300 mV for a 90-nm test chip. Operating at 330 mV provides minimum energy per cycle at 9/spl times/ less energy than ideal shutdown for reduced performance scenarios. Measurements from the test chip characterize the impact of temperature on the minimum energy point.

A Batteryless 19

This paper presents an ultra-low power batteryless energy harvesting body sensor node (BSN) SoC fabricated in a commercial 130 nm CMOS technology capable of acquiring, processing, and transmitting electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG) data. This SoC utilizes recent advances in energy harvesting, dynamic power management, low voltage boost circuits, bio-signal front-ends, subthreshold processing, and RF transmitter circuit topologies. The SoC is designed so the integration and interaction of circuit blocks accomplish an integrated, flexible, and reconfigurable wireless BSN SoC capable of autonomous power management and operation from harvested power, thus prolonging the node lifetime indefinitely. The chip performs ECG heart rate extraction and atrial fibrillation detection while only consuming 19 μW, running solely on harvested energy. This chip is the first wireless BSN powered solely from a thermoelectric harvester and/or RF power and has lower power, lower minimum supply voltage (30 mV), and more complete system integration than previously reported wireless BSN SoCs.

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Well-designed circuits are one key ldquoinsulatingrdquo layer between the increasingly unruly behavior of scaled complementary metal-oxide-semiconductor devices and the systems we seek to construct from them. As we move forward into the nanoscale regime, circuit design is burdened to ldquohiderdquo more of the problems intrinsic to deeply scaled devices. How this is being accomplished is the subject of this paper. We discuss new techniques for logic circuits and interconnect, for memory, and for clock and power distribution. We survey work to build accurate simulation models for nanoscale devices. We discuss the unique problems posed by nanoscale lithography and the role of geometrically regular circuits as one promising solution. Finally, we look at recent computer-aided design efforts in modeling, analysis, and optimization for nanoscale designs with ever increasing amounts of statistical variation.

W MICS/ISM-Band Energy Harvesting Body Sensor Node SoC for ExG Applications

A 256kb sub-threshold SRAM operates below 400mV from 0 to 85degC and is implemented in 65nm CMOS technology. For the same 6sigma static-noise margin, the sub-threshold SRAM at 0.4V achieves 2.25-times lower leakage power and 2.25-times lower active energy than its 6T counterpart at 0.6V. The SRAM uses a 10T bitcell to enable sub-threshold functionality

Digital Circuit Design Challenges and Opportunities in the Era of Nanoscale CMOS

This paper analyzes write ability for SRAM cells in deeply scaled technologies, focusing on the relationship between static and dynamic write margin metrics. Reliability has become a major concern for SRAM designs in modern technologies. Both local mismatch and scaled VDD degrade read stability and write ability. Several static approaches, including traditional SNM, BL margin, and the N-curve method, can be used to measure static write margin. However, static approaches cannot indicate the impact of dynamic dependencies on cell stability. We propose to analyze dynamic write ability by considering the write operation as a noise event that we analyze using dynamic stability criteria. We also define dynamic write ability as the critical pulse width for a write. By using this dynamic criterion, we evaluate the existing static write margin metrics at normal and scaled supply voltages and assess their limitations. The dynamic write time metric can also be used to improve the accuracy of VCCmin estimation for active VDD scaling designs.

A 256kb Sub-threshold SRAM in 65nm CMOS

Multithreshold CMOS (MTCMOS) circuits reduce standby leakage power with low delay overhead. Most MTCMOS designs cut off the power to large blocks of logic using large sleep transistors. Locally distributing sleep devices has remained less popular even though it has several advantages described in this paper. However, locally placed sleep devices are only feasible if sneak leakage currents are prevented. This paper makes two contributions to leakage reduction. First, we examine the causes of sneak leakage paths and propose a design methodology that enables local insertion of sleep devices for sequential and combinational circuits. A set of design rules allows designers to prevent most sneak leakage paths. A fabricated 0.13-/spl mu/m, dual V/sub T/ test chip employs our methodology to implement a low-power FPGA architecture with gate-level sleep FETs and over 8/spl times/ measured standby current reduction. Second, we describe the implementation and benefits of local sleep regions in our design and examine the interfacing issues for this technique. Local sleep regions reduce leakage in unused circuit components at a local level while the surrounding circuits remain active. Measured results show that local sleep regions reduce leakage in active configurable logic blocks (CLBs) on our chip by up to 2.2/spl times/ (measured) based on configuration.