5 research outputs found

    Design and analysis of two low power sram cell structures

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    In this paper, two static random access memory (SRAM) cells that reduce the static power dissipation due to gate and subthreshold leakage currents are presented. The first cell structure results in reduced gate voltages for the NMOS pass transistors, and thus lowers the gate leakage current. It reduces the subthreshold leakage current by increasing the ground level during the idle (inactive) mode. The second cell structure makes use of PMOS pass transistors to lower the gate leakage current. In addition, dual threshold voltage technology with forward body biasing is utilized with this structure to reduce the subthreshold leakage while maintaining performance. Compared to a conventional SRAM cell, the first cell structure decreases the total gate leakage current by 66% and the idle power by 58% while the second cell structure reduces the total gate leakage current by 27% and the idle power by 37% with no access time degradation

    An asymmetric SRAM cell to lower gate leakage

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    We introduce a new Static Random Access Memory (SRAM) cell that offers high stability and reduces gate leakage power in caches while maintaining low access latency. Our design exploits the strong bias towards zero at the bit level exhibited by the memory value stream of ordinary programs. Compared to conventional symmetric high-performance cell, our new cell reduces total leakage by more than 24 % in the zero state at high temperature. With one cell design, total cache leakage is reduced by 24% at high temperature with no performance or stability loss. At low temperatures, where gate leakage is dominant, our cell reduces total cache leakage by 43%. We show that the new cell can be combined in an orthogonal fashion with asymmetric dual-Vt cells to lower both gate and subthreshold leakage, reducing total leakage by 45 % to 60 % with comparable performance and stability.

    Low energy digital circuit design using sub-threshold operation

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2006.Includes bibliographical references (p. 189-202).Scaling of process technologies to deep sub-micron dimensions has made power management a significant concern for circuit designers. For emerging low power applications such as distributed micro-sensor networks or medical applications, low energy operation is the primary concern instead of speed, with the eventual goal of harvesting energy from the environment. Sub-threshold operation offers a promising solution for ultra-low-energy applications because it often achieves the minimum energy per operation. While initial explorations into sub-threshold circuits demonstrate its promise, sub-threshold circuit design remains in its infancy. This thesis makes several contributions that make sub-threshold design more accessible to circuit designers. First, a model for energy consumption in sub-threshold provides an analytical solution for the optimum VDD to minimize energy. Fitting this model to a generic circuit allows easy estimation of the impact of processing and environmental parameters on the minimum energy point. Second, analysis of device sizing for sub-threshold circuits shows the trade-offs between sizing for minimum energy and for minimum voltage operation.(cont.) A programmable FIR filter test chip fabricated in 0.18pum bulk CMOS provides measurements to confirm the model and the sizing analysis. Third, a low-overhead method for integrating sub-threshold operation with high performance applications extends dynamic voltage scaling across orders of magnitude of frequency and provides energy scalability down to the minimum energy point. A 90nm bulk CMOS test chip confirms the range of operation for ultra-dynamic voltage scaling. Finally, sub-threshold operation is extended to memories. Analysis of traditional SRAM bitcells and architectures leads to development of a new bitcell for robust sub-threshold SRAM operation. The sub-threshold SRAM is analyzed experimentally in a 65nm bulk CMOS test chip.by Benton H. Calhoun.Ph.D
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