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Leakage in Nanometer CMOS Technologies by Siva G. Narendra

By Siva G. Narendra

Scaling transistors into the nanometer regime has led to a dramatic elevate in MOS leakage (i.e., off-state) present. Threshold voltages of transistors have scaled to take care of functionality at decreased strength offer voltages. Leakage present has develop into a massive section of the full energy intake, and in lots of scaled applied sciences leakage contributes 30-50% of the general strength intake below nominal working stipulations. Leakage is critical in a number of various contexts. for instance, in machine purposes, lively leakage strength (i.e., leakage strength whilst the processor is computing) is changing into major in comparison to switching energy. In battery operated platforms, standby leakage (i.e., leakage whilst the processor clock is became off) dominates as strength is drawn over lengthy idle sessions. elevated transistor leakages not just influence the general energy ate up through a CMOS method, but additionally decrease the margins to be had for layout as a result of robust courting among procedure edition and leakage energy. it's crucial for circuit and process designers to appreciate the parts of leakage, sensitivity of leakage to diversified layout parameters, and leakage mitigation suggestions in nanometer applied sciences. This publication presents an in-depth remedy of those concerns for researchers and product designers.

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B=l tOE-t03 1 10 100 1000 10000 Time (ns) Figure 2-11. Transient behavior of leakage current convergence time constant in a 2 NMOS stack under different temperature and initial input conditions. 0 20 40 60 80 100 Vt - reduction (mV) Figure 2-12, Dependence of leakage convergence time constant of stack leakage on threshold voltage, temperature, and initial input conditions. T = SO^C 0 25 50 75 Vt rediiction(mV) Figure 2-13. Leakage current increase with threshold voltage reduction at the transistor and adder block levels.

Back to the simulated data, the time required for the leakage current in transistor stacks to converge to its final value is dictated by the rate of charging or discharging of the capacitance at the intermediate node by the sub-threshold drain current of Ml or M2. This time constant as shown in Figure 2-11 is, therefore, determined by drain-body junction and gateoverlap capacitances per unit width, the input conditions immediately before the stack transistors are turned OFF, and transistor sub-threshold leakage current, which depends strongly on temperature and Vf Therefore, the convergence rate of leakage current in transistor stacks increases rapidly with Vt reduction and temperature increase, as shown in Figure 2-11 and Figure 2-12.

These methods begin with the approach of sizing the local sleep devices to meet the same performance constraint. Keeping the sleep devices separate at the local level allows CAD algorithms to relax the performance constraint for local gates while meeting the global constraint. One new approach uses local sleep devices at the gate level without any clustering [18]. This method sizes the sleep transistors to meet a global delay requirement by taking up all of the available slack in the design. This means that the delay for many individual gates increases more than the global constraint, but the total worst-case delay meets the constraint.

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