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Stability and Leakage Analysis of a Novel PP Based 9T SRAM Cell Using N Curve at Deep Submicron Technology for Multimedia Applications

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Due to continuous scaling of CMOS, stability is a prime concerned for CMOS SRAM memory cells. As scaling will increase the packing density but at the same time it is affecting the stability which leads to write failures and read disturbs of the conventional 6T SRAM cell. To increase the stability of the cell various SRAM cell topologies has been introduced, 8T SRAM is one of them but it has its limitation like read disturbance. In this paper we have analyzed a novel PP based 9T SRAM at 45 nm technology. Cell which has 33% increased SVNM (Static Voltage Noise Margin) from 6T and also 22% reduced leakage power. N curve analysis has been done to find the various stability factors. As compared to the 10T SRAM cell it is more area efficient.
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Circuits and Systems, 2011, 2, 274-280
doi:10.4236/cs.2011.24038 Published Online October 2011 (http://www.scirp.org/journal/cs)
Copyright © 2011 SciRes. CS
Stability and Leakage Analysis of a Novel PP Based 9T
SRAM Cell Using N Curve at Deep Submicron Technology
for Multimedia Applications
Shilpi Birla1*, Rakesh Kumar Singh2, Manisha Pattanaik3
1Department of Electronics and Communication (ECE), Sir Padampat Singhania University (SPSU), Udaipur, India
2Department of Electronics and Communication (ECE), Bipin Tripathi Kumaon Institute of
Technology (BTKIT), Dwarahat Almora, India
3VLSI Group, Atal Bihari Vajpayee Indian Institute of
Information Technology & Management (ABV-IIITM), Gwalior, India
E-mail: *shilpibirla@gmail.com
Received July 22, 2011; revised August 10, 2011; accepted August 17, 2011
Abstract
Due to continuous scaling of CMOS, stability is a prime concerned for CMOS SRAM memory cells. As
scaling will increase the packing density but at the same time it is affecting the stability which leads to write
failures and read disturbs of the conventional 6T SRAM cell. To increase the stability of the cell various
SRAM cell topologies has been introduced, 8T SRAM is one of them but it has its limitation like read dis-
turbance. In this paper we have analyzed a novel PP based 9T SRAM at 45 nm technology. Cell which has
33% increased SVNM (Static Voltage Noise Margin) from 6T and also 22% reduced leakage power. N curve
analysis has been done to find the various stability factors. As compared to the 10T SRAM cell it is more
area efficient.
Keywords: N Curve, Scaling, SVNM (Static Voltage Noise Margin), Leakage Power, 9T SRAM Cell
1. Introduction
The high demand of increasing packaging density and
low power SRAMs for multimedia applications leads to
the problem of data stability. As ultra low power supply
voltages suppresses power consumption, gate leakage
and stand by current which results in increase of life time
of battery. Various Read & Write assist methods were
introduced to enhance the write margin and read stability
of 6T Cells. Some of the techniques are CVDD (Cell
Vdd) adjustment, CVSS (Cell virtual ground), dual rail
power supply, negative bitline etc. But still the voltage of
the conventional 6T SRAM cannot be reduced beyond
0.6 V for successful operation. Various topologies of
SRAM cell has been introduced, 7T SRAM cell in which
a read static noise margin is achieved by cutting off a
pull down path during read operation but has limited
write capability due to single end write operations [1].
8T SRAM cell which is one of the popular topology
which increases the stability but has its own limitation.
In this paper the limitation of 8T has been removed and
alternative topologies have been discussed to increase the
stability [2]. Although other 9T SRAM cell as in [3] is
also been discussed but it suffers from read disturbance.
As far as best of my knowledge this cell has not been
reported yet.
In section II various factors of SRAM functional Mar-
gins has been reported. In section III the novel PP based
9T SRAM cell has been explained in detail. In section IV
N curve has been discussed. In section V the analysis of
various stability parameters with respect to Vdd and
temperature has been discussed. In section VI the leak-
age power of the proposed cell has been discussed and in
the end conclusion.
2. SRAM Functional Margins
SRAM functional margins are determined by three
SRAM design Parameters: static noise margin (SNM),
write margin (WRM), and cell current (Icell). Since all of
them strongly depend on operating voltage (VDD), tran-
sistor channel length (Lg), and width (Wg). So the cell
stability depends on the amount of VT mismatch caused
by the random variation (σVT) of threshold voltage VT
S. BIRLA ET AL.275
and operation voltage VDD as well as cell ratios: γ-ratio
for write and β-ratio for read [4].
2.1. Static Noise Margin
The static noise margin (SNM) is the maximum amount
of noise voltage VN that can be tolerated at the both in-
puts of the cross-coupled inverters in different directions
while inverters still maintain bi-stable operating points
and cell retains its data [5]. In other words, the static
noise margin (SNM) quantifies the amount of noise vo-
ltage VN required at the storage nodes of SRAM to flip
the cell data. The cell becomes more vulnerable to noise
during a read access since the “0” storage node rises to a
voltage higher than ground (GND) due to a voltage divi-
sion along the Pass gate transistors and inverter Pull-
down devices between the pre-charged BL and the GND
terminal of the cell. The ratio of the transistor width of
Pull-down to Passgate, commonly referred to as the
β-ratio determines how high the “0” storage node rises
during a read access [4] as shown in Figure 1 for con-
ventional 6T SRAM cell. Due to the scaling of the device
to nanometer regime, the variation of β-ratio is signifi-
cantly increased. This is the primary reason for increas-
ing SNM challenge in nanometer-scale SRAM. The ratio
of inverter pull-down transistors (M1 or M2) and pull-up
transistors (M3 or M4) also directly impacts the cell im-
munity to noise. Weaker pull-up due to the variations
makes the cell easier to flip as lowering its trip point of
inverter, making the cell more vulnerable to noise.
When the WL is off, the SNM becomes larger than
that for read access because of no rising of “0” storage
node from GND level [4]. The two kinds of SNMs for
data retention and read access are referred to as “hold
SNM margin” and “read SNM margin” [6].
2.2. Write Margin
The cell data is written by forcing the BL pair to the dif-
ferential levels of “1” and “0” while WL is asserted to
allow pass gate transistors (M5 or M6) connected to the
BL. The potential of the corresponding storage node is
pulled down to the critical level that is dependent on the
ratio of transistor strengths between M5 and M3 (or M6
and M4). This ratio is referred to as γ -ratio. In order to
ensure robust write operation, the critical level has to be
lowered than the trip point of connected inverter before
the level of “0” written BL is reached to the end-point
(e.g., GND). The write margin (WRM) is defined as the
rest of potential difference between the BL level at which
the data is flipped and the end-point (e.g., GND) as
shown in Figure 1. If the cell data is flipped when the
BL comes at X mV, where X mV is allowed to reach to
the GND level, WRM is defined as X mV. As the device
sizes of Pass gate and Pull-up are scaled down to nano-
meter regime, the variation of γ-ratio is significantly in-
creased. That is the reason why WRM has become just as
difficult as read in nanometer-scale SRAM [7].
2.3. Cell Current (Icell)
The BL discharging time takes a large percentage of the
total access time. The discharging time (TBL) depends
on the BL capacitance, the cell current, and the required
BL discharging level (VSEN). The amount of cell cur-
rent (Icell) is determined by the strength of passgate and
pull-down connected in series between the BL and GND
as shown in Figure 1. The higher VT settings for pass
gate, pull-down, and pull-up transistors in SRAM can
suppress the sub-threshold leakage but it causes not only
the reduction of Icell but also increases its variation [5].
3. Proposed Novel PP Based 9T Cell
In this paper we have proposed a novel PP based 9T
SRAM Cell Figure 2. In this cell one extra signal RWL
is used during read operation, during read operation we
keep it at gnd voltage otherwise the value remains high.
The true storage nodes are separated from the two virtual
storage nodes connected between the stacked PMOS. If
we look at the figure we will find that there is one extra
NMOS transistor is used which creates a discharging
path. It is connected to the RWL. The discharging path is
used such that to discharge a precharged high bitline
during the read operation.
This circuit has certain advantages like it does not
have read problem as the discharging path is isolated
from the true storage nodes. The write ability is also not
disturbed in this structure. We have used a single word-
line for both the operations read and write .This cell has
better stability and it is power efficient.
3.1. Detailed Structure of the Cell
In this section, we describe our cell design in Figure 2.
As mentioned previously, it is composed of two cross
coupled P-P-N inverters, and data is stored in node Q and
Figure 1. Conventional 6T SRAM cell.
Copyright © 2011 SciRes. CS
S. BIRLA ET AL.
276
Figure 2. Proposed PP based 9T SRAM cell.
node Qb in a complementary manner. Transistors P1,
PP3, and ND1 form a P-P-N inverter and P1, PP4, ND2
form another.
ND1 provides the read current path for discharging a
bitline (BL) or its complementary (BLB), depending on
the stored values of Q and Qb, respectively. The source
terminal of this transistor is connected to the VGND pin,
which connects to the ground voltage only during the
read operation. Anytime else, it stays high to curb un-
necessary leakage current.V1 and V2 are located betw-
een the two cascaded P-MOS transistors forming the
P-P-N inverter. Q and Qb are the storage nodes .BL and
BLB are bitlines while Wl is the word line as in conven-
tional 6T SRAM cell.
3.2. Working of the Novel 9T Cell
3.2.1. Write Operation
During a write operation .initially in this PP based 9T
SRAM Figure 2, storage node Q stores “0” while Qb
stores “1”. To perform a write operation, the wordline
WL is enabled and one bitline, e.g., BLB, is pulled down
to ground in advance. When the supply voltage is rela-
tively high (e.g., 1 V), node Qb (storing “1”) here in this
case will be pulled down directly through the discharging
path formed by. In turn, node Q will be charged up to
complete the data-flipping process.
In general, the lower portion of our P-P-N inverter pair
can be viewed as a latch consisting of PP3-ND1and PP4-
ND2. In some sense, this latch takes node V1and node V2
as the pseudo supply terminals. In step 1, Qb is pulled
down quickly to nearly the ground voltage at the begin-
ning of the write operation since it is driven by BLB tied
to strong “0”. Qb via the PMOS between them (PP3),
reducing the voltage of Qb to a lower middle voltage.
During this time period, PP3 and PP4 controlled by Qb
still conducts weakly to pull up voltage at node Q, Due to
the coupling effect of parasitic capacitances the voltage of
Qb, which is in the floating state, rises with node Q but
only slightly. In step 2, the data flipping finally takes
place when Q is strong enough to conduct the PDR tran-
sistor to discharge Qb down to the ground voltage.
It is worth mentioning that even though such a write
mechanism takes relatively longer time to accomplish the
data flipping, it is still shorter than the read access time,
and therefore, overall it does not introduce any operating
frequency penalty. We can also further improve the cell’s
write-ability by strengthening the access transistors
(NA1 and NA2). It does not affect the read performance.
3.2.2. Read Operation
To perform a read operation, the wordline WL is enabled
and RWL is pulled down to ground to allow bitline dis-
charging. Assuming that the data stored at Q is now “0”.
Since data node Q and Qb are isolated from bitline BL
by PP2 and PP3 (which is between the true storage node
Q) and thus the so-called read current (which is the cur-
rent used to discharge a bitline) does not flow through
the storage node Qb but through the bypassing ND3 as
indicated in Figure 2. This is the main reason why the
read stability does not degrade at all in our cell. As for a
6T cell, the read current flows through the storage node
directly, thereby causing read disturbance, i.e., the volt-
age at data node Q will rise temporarily. This will de-
grade the read stability because the cell flipping will be
more likely to take place.
The pull-up transistors P1 and P2 are usually made
weaker for easy write operation just like in a conven-
tional 6T cell. While the pull-down transistors ND1 and
ND2, forming the cell discharging paths, need to be str-
onger to facilitate a larger read current and thereby a
quicker access. The pass gate transistors NA1 and NA2
need to be strong enough to serve as high-conduction pa-
ths between the accessed cell and the bitlines during both
the read and write operations. The two pull-up transistors,
PP2 and PP3, need to be slightly stronger, to compensate
for the conductivity degradation of the cascaded PMOS
structure linking the storage nodes (i.e., Q and Qb) and
Vdd, which help contribute to a good hold SNM. Unlike
a 6T cell, the pull-down transistors do not have to be
strong, since they do not involve in the cell discharging
paths. However, their strengths are made comparable to
the cascaded PMOS structure mentioned above to ach-
ieve a more balanced cell structure which could lead to a
larger hold SNM.
In our cell we have seen that the SVNM has been
1.53times greater than that of conventional 6T cell. In
our cell we achieved 460mv while for 6T it is 300 mv.
The leakage power has also been reduced by 3.3 times
than that of conventional 6T.
Copyright © 2011 SciRes. CS
S. BIRLA ET AL.277
4. Stability Measurement: N Curve Analysis
Numerous analytical models of the static noise margin
(SNM) have been developed to optimize the cell design,
to predict the effect of parameter changes on the SNM
and to assess the impact of intrinsic parameter variations
on the cell stability. Furthermore, new SRAM cell circuit
designs have been developed to maximize the cell stabil-
ity for future technology nodes [8]. The set up for N curve
is as shown in Figure 3. In an ideal case, each of the two
cross-coupled inverters in the SRAM cell has an infinite
gain. As a result, the butterfly curves delimit a maximal
square side of maximum, being an asymptotical limit for
the SNM. Therefore, scaling limits the stability of the cell.
An additional drawback of the SNM is the inability to
measure the SNM with automatic inline testers [4], due to
the fact that after measuring the butterfly curves of the
cell the static current noise margin (SINM) still has to be
derived by mathematical manipulation of the measured
data. An alternative definition for the SRAM read stabi-
lity is based on the N-curve of the [5]. N-curve contains
information both on the read stability and on the write-
ability, thus allowing a complete functional analysis of
the SRAM cell with only one N-curve [8].
Parameters which are find by using N curve these 4
parameters are useful for measuring the write ability and
read ability of the cell.
The static voltage noise margin (SVNM)
The static voltage noise margin is the voltage differ-
ence between points A and B in Figure 4 and it indicates
the maximum tolerable DC noise voltage at the input of
the inverter of the cell before its content changes [4].
The static current noise margin (SINM)
The static current noise margin is defined as the maxi-
Figure 3. Set up for N curve analysis.
Figure 4. Ncurve for 6 T SRAM cell [2].
mum value of DC current that can be injected in the
SRAM cell before its content changes [4]. It is given by
the peak value of Iin during read operation that is be-
tween points A and B in the Figure 4.
The Write Trip Voltage (WTV)
The SRAM N-curve also provides information re-
garding the write ability of the cell. WTV is the voltage
drop needed to flip the internal node “1” of the cell with
both the bit lines clamped at Vdd [4]. It is given by the
voltage difference between the second (B) and the last
zero crossing point (C) in Figure 4.
The Write Trip Current (WTI)
It is the amount of current needed to write the cell
when both bit lines are clamped at supply voltage equal
to Vdd [5]. The peak value of Iin after the second zero
crossing of N-curve gives WTI.
For better read stability, the values of SVNM, and the
magnitude of SINM and hence the value of static power
noise margin SPNM (product of mean of SVNM and
mean of SINM) should be larger. For better write ability
the value of WTV, the absolute value of WTI and hence
the value of WTP (product of mean of WTV and mean of
WTI) must be smaller.
5. Analysis of N Curve Metrics
N-curve analysis has been done at 45nm technology in
order for low voltage operation. Various factors of sta-
bility has been analyses with the affect of temperature
and voltage on them. Figure 5 shows one N curve analy-
sis at Vdd = 1 V at temperature varies from –25˚C to
125˚C [2].
5.1. Effect of Power Supply (Vdd)
We have seen that there is significant affect of power
supply on the 4 parameters which we have obtained from
the Ncurve.As Vdd increases the stability also increases
[9]. This is also been observed here that as the Vdd in-
creased the SINM, WTV, SVNM and WTI the four pa-
rameters has been increased as shown in the given
graphs.
5.1.1. Effect on SVNM
As shown in the graph Figure 6, we see that at Vdd = 1
V it is maximum 460 mv and reduces when we go to
Vdd = 0.6 V. As we know that SVNM it is the maximum
DC tolerable voltage before the cell changes it contents
so it means that as Vdd reduces the cell tolerance is also
reduces.
5.1.2. Effect on WTI
As discussed above the write-trip current (WTI) is the
Copyright © 2011 SciRes. CS
S. BIRLA ET AL.
Copyright © 2011 SciRes. CS
278
Figure 5. N curve of 9T SRAM cell.
amount of current needed to write the cell when both
bit-lines are kept at Vdd . This is the current margin of
the cell for which its content changes as in (Figure 7).
The ability to write a cell with both bit-lines clamped at
results actually in a destructive read operation; therefore,
the absolute value of WTI should be large enough to
cope with the read stability requirement. On the other
hand, the lower the absolute WTI is, the higher the
write-trip point of the cell. It shows an exponential rela-
tion with Vdd. WTI is measure at various temperatures.
5.1.3. Effect on WTV
Write-trip voltage (WTV) is the voltage drop needed to
flip the internal node “1” of the cell with both the
bit-lines clamped at Vdd. Write ability requires both
WTI and WTV.WTV increases with Vdd. At 1 V the cell
has maximum stability and it decreases drastically when
the Vdd reaches to 0.6 V. As shown in Figure 8.
5.1.4. Effect on SINM
By using the combined SVNM and SINM, the read sta-
bility criteria for the cell are defined properly. For exam-
ple, a small SVNM combined with a large SINM will
still result in a stable cell since the amount of required
noise charged disturb the cell is large. At Vdd 1V we
have good SINM but it reduces exponentially at Vdd =
0.6 V, as shown in Figure 9.
5.2. Effect of Temperature
As we have varied the temperature from 0˚C to 125˚C
we have seen that the SVNM and WTV is unaffected by
the temperature variation but the currents i.e. the write
trip current and static noise margin current has been af-
fected by temperature variation. As temperature in-
creases both the SINM and WTI reduces. As shown in
Figures 10 and 11 respectively. The variation has been
observed at varying Vdd from 1 V to 0.6 V.
6. Analysis of Leakage Current for Proposed
Cell
In this cell we have achieved 33% less leakage power
with respect to 6T SRAM cell, as in this cell we have
used the PMOS cell and also we used ND3 which is used
to reduced the leakage power. We have seen the affect of
Vdd and temperature on leakage power. As we know it
depends exponential to Temperature and increases with
temperature the same affect is seen here Figure 12. It
also shows the effect of Vdd which shows that there is
7X increases in Leakage current when we increase the
Vdd from 0.6 V to Vdd 1 V.
We have also analyzed the Leakage power with SINM
as shown in Figure 13 and found that as SINM increases
the Leakage power also increases which shows that with
increasing Vdd the SINM increases and at the same time
increasing Vdd results in increasing the leakage power
[10].
7. Conclusions
We have proposed a novel 9T SRAM cell which has
S. BIRLA ET AL.279
Figure 6. Vdd vs. SVNM.
Figure 7. Vdd vs. WTI.
Figure 8. Vdd vs. WTV.
Figure 9. Vdd vs. SINM.
Figure 10. Temperature vs. SINM.
Figure 11. Temperature vs. WTI.
Figure 12. Temperature vs. leakage current.
Figure 13. Leakage power vs. SINM.
Copyright © 2011 SciRes. CS
S. BIRLA ET AL.
Copyright © 2011 SciRes. CS
280
been simulated at 45 nm 65% increase in SVNM compa-
red to 6T SRAM cell. The cell has 33% leakage power
reduction also with respect to 6T SRAM cell and in this
we have not used any leakage reduction techniques. So
the future expansion can be done by sizing the cell to in-
crease the stability i.e. the write ability and read ability
of the cell. Also power can be reduced by using various
leakage reduction methods. Although the area with resp-
ect to 6T has been increased but at lower technology it is
comparable to 6T. The SNM measured is 380mv which
can be improved by sizing the transistor widths.
8. Acknowledgements
The authors are very grateful to the respective organiza-
tion for their support and encouragement.
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Chapter
The limitation with the existing testing techniques is, if the test does not consider all the aspects of SRAM parameters, including parasitic memory effect, then it will result as an incomplete test. This paper presents a new parasitic extraction testing method for embedded SRAMs, employing defect-induced layout. The defect injection in a circuit is due to an open/short between wires, or missing contacts etc. In this work, only node-to-node short defects are considered. Our test results proved that using parasitic extraction method existing faults as well as undefined faults could be detected. The existing faults identified are Stuck At Fault, (SAF), Undefined Read Fault (URF), Read Destructive Fault (RDF), Undefined Write Fault (UWF), Random Read Fault (RRF), Incorrect Read Fault (IRF), and No Access Fault (NAF). The undefined faults identified are Bit-Line Delay Fault (BDF), Initialization Order Fault (IOF), Un Stabilized Write Fault (USWF), Un Stabilized Read Fault (USRF), and Write Before Access Fault (WBAF). In addition, the complete fault model dictionary is also an outcome of this work.
Conference Paper
Improving the Noise margin is one of the important challenge in every state of the art SRAM design. Due to the Process variations like threshold voltage variations, supply voltage variations etc.. in scaled technologies, stable operation of the bit cell is critical to obtain with high yield in low-voltage SRAM. In this paper a new assist technique (Read assist and write assist) is proposed to enhance the read and write margins of the 6T SRAM bit cell and the same write assist circuit is applicable to enhance the write margin of the 8T SRAM bit cell. The simulations are performed in 90nm TSMC process Technology node and the read and write margin simulation results are compared with different SRAM circuits like 6T SRAM bit cell with cell ratio of 1, 2, 3 and Dynamic word line swing technique and 8T SRAM bit cell. The effect of temperature and threshold voltage values on Read and Write margins are observed. By using the proposed read assist technique the read margin is improved by 2.375 times for 6T cell and with write assist technique the write margin is improved by 1.89 times for 6T and 8T cells.
Conference Paper
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SRAM stability during word line disturb (access disturb) is becoming a key constraint for V<sub>DD</sub> scaling (Burnett, 1994). In this paper we present a design methodology for SRAM stability during access disturb. In this methodology, the SRAM access disturb margin (ADM) is defined as the ratio of the magnitude of the critical current to maintain SRAM stability (I<sub>CRIT</sub>) to the sigma of I<sub>CRIT</sub>. Using ADM as a figure of merit, this methodology enables one to project the cell stability margin due to process variations, e.g. V<sub>T</sub> variation, during design of a SRAM cell. Using statistical analysis, the required stability margin for an application requirement such as array size and available redundancy can be estimated. Direct cell probing and array test can be used to verify that the stability target is met.
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Data stability of SRAM cells has become an important issue with the scaling of CMOS technology. Memory banks are also important sources of leakage since the majority of transistors are utilized for on-chip caches in today's high performance microprocessors. A new nine-transistor (9T) SRAM cell is proposed in this paper for simultaneously reducing leakage power and enhancing data stability. The proposed 9T SRAM cell completely isolates the data from the bit lines during a read operation. The read static-noise-margin of the proposed circuit is thereby enhanced by 2 X as compared to a conventional six-transistor (6T) SRAM cell. The idle 9T SRAM cells are placed into a super cutoff sleep mode, thereby reducing the leakage power consumption by 22.9% as compared to the standard 6T SRAM cells in a 65-nm CMOS technology. The leakage power reduction and read stability enhancement provided with the new circuit technique are also verified under process parameter variations.
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SRAM cell read stability and write-ability are major concerns in nanometer CMOS technologies, due to the progressive increase in intra-die variability and V<sub>dd</sub> scaling. This paper analyzes the read stability N-curve metrics and compares them with the commonly used static noise margin (SNM) metric defined by Seevinck. Additionally, new write-ability metrics derived from the same N-curve are introduced and compared with the traditional write-trip point definition. Analytical models of all these metrics are developed. It is demonstrated that the new metrics provide additional information in terms of current, which allows designing a more robust and stable cell. By taking into account this current information, V<sub>dd</sub> scaling is no longer a limiting factor for the read stability of the cell. Finally, these metrics are used to investigate the impact of the intra-die variability on the stability of the cell by using a statistically-aware circuit optimization approach and the results are compared with the worst-case or corner-based design
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This paper presents a novel SRAM circuit technique for simultaneously enhancing the cell operating margin and improving the circuit speed in low-voltage operation. During each access, the wordline and cell power node of selected SRAM cells are internally boosted into two different voltage levels. This technique with optimized boosting levels expands the read margin and the write margin to a sufficient amount without an increase of cell size. It also improves the SRAM circuit speed owing to an increase of the cell read-out current. A 256 Kbit SRAM test chip with the proposed technique has been fabricated in a 0.18 μm CMOS logic process. For 0.8 V supply voltage, the design scheme increases the cell read margin by 76%, the cell write margin by 54% and the cell read-out current by three times at the expense of 14.6% additional active power. Silicon measurement eventually confirms that the proposed SRAM achieves nearly 1.2 orders of magnitude reduction in a die bit-error count while operating with 26% faster speed compared with those of conventional SRAM.
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The increased importance of lowering power in memory design has produced a trend of operating memories at lower supply voltages. Recent explorations into sub-threshold operation for logic show that minimum energy operation is possible in this region. These two trends suggest a meeting point for energy-constrained applications in which SRAM operates at sub-threshold voltages compatible with the logic. Since sub-threshold voltages leave less room for large static noise margin (SNM), a thorough understanding of the impact of various design decisions and other parameters becomes critical. This paper analyzes SNM for sub-threshold bitcells in a 65-nm process for its dependency on sizing, V<sub>DD</sub>, temperature, and local and global threshold variation. The V<sub>T</sub> variation has the greatest impact on SNM, so we provide a model that allows estimation of the SNM along the worst-case tail of the distribution
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