I. INTRODUCTION
Recently, deep learning has been widely adopted in mobile electronic devices for applications
such as image or speech recognition. The mobile devices accept the input data, send
them to cloud computers via a wireless communication network for deep-learning processing,
receive the processed data from the cloud computers, and display images or generate
sounds at the mobile devices for the received data [1,2]. This method has a latency problem associated with wireless communication to and
from cloud computers. Also, data privacy is an issue in this method, because all the
user data are sent to a cloud computer for deep learning processing. To avoid latency
and privacy issues, on-device deep-learning mobile devices are actively studied at
the research level [3,4]. The on-device deep learning requires a large-size memory with high bandwidth as
well as a fast processing element with high processing power; a commercial dynamic
random access memory (DRAM) chip is the most suitable memory for this application.
Hence, the on-device deep-learning hardware mostly consists of an application-specific
integrated circuit (ASIC) chip and commercial DRAM chips; the ASIC chip includes a
processing element and a DRAM controller circuit [5,6].
The DRAM controller performs three major functions; an initialization operation, a
data read/write operation, and a refresh operation. After the system power-on reset,
the DRAM controller goes through the initialization operation by setting the internal
registers of the DRAM chip in accordance with the application, calibrating the on-die
termination resistance of the DRAM chip and the DRAM controller, and calibrating the
delay lines of the DRAM controller to match the delay times of the clock (CK), strobe
(DQS) and 8 data (DQ) paths to and from the DRAM chip. After the initialization operation,
the DRAM controller can write or read data to or from the DRAM chip. To write or read
data, the DRAM controller sends addresses to the DRAM chip in two steps; firstly,
the row and bank addresses along with the bank activate command (RASN, CASN, WEN =
0, 1, 1) to open the page, secondly, the column address along with the write (RASN,
CASN, WEN = 1, 0, 0) or read (RASN, CASN, WEN = 1, 0, 1) command. After sending the
addresses, the DRAM controller sends or receives DQ and DQS to and from the DRAM chip.
At the end of an operation for a row and bank address, the DRAM controller issues
the bank precharge command (RASN, CASN, WEN = 0, 1, 0) to precharge all the bit lines
of the accessed bank to 0.5 VDDQ. Each DRAM cell in a DRAM chip is required to refresh
at every 64 ms. The refresh interval of 64 ms is divided into 8192 refresh steps;
each refresh step occurs at every 7.8125 us and takes 350 ns (tRFC) to read 8 rows
in all 8 banks for the 8 Gb double data rate 3 (DDR3) DRAM case. The DRAM controller
can write or read data for around 7.4 us during a refresh interval of 7.8125 us.
There are three issues to be considered in implementing the DRAM controller in an
ASIC chip for on-device deep learning.
The first issue is that the DRAM controller requires many pin counts to communicate
with commercial DRAM chips. For example, the DRAM controller for a 16 DQ 8 Gb DDR3
DRAM chip needs 48 pins for signaling (16 DQ, 4 DQS, 16 address, 3 bank address, 2~CK,
7 commands (RASN, CASN, WEN, CSN, CKE, ODT, RESETN)) [7].
The second issue is that the DRAM controller occupies a significant portion of the
ASIC chip area. The large pin count increases chip area because each I/O signal requires
a large buffer circuit.
The third issue, the most important one, is that the DRAM and the DRAM controller
consume a large power; the DRAM and the DRAM controller consume 41 ~ 59% in [8] and 50 ~ 70% in [9] of the total power in on-device deep learning applications. Because the DRAM interface
uses a high data rate, termination is required at the transceiver to reduce reflection.
The DDR3 SDRAM chip uses on-die termination resistors of 60 ${\Omega}$ for write and
34 ${\Omega}$ for read operations in default, respectively, by following the Joint
Electron Device Engineering Council (JEDEC) standard [7]. Due to the termination, the transceiver consumes large static power; the transceiver
blocks of the DRAM controller and the DRAM chip consume 110 mW and 67 mW, respectively
[10]. Because the static power of the transceiver is inversely proportional to the termination
resistance, we can reduce the static power by increasing the on-die termination resistance
[11]. Increasing the termination resistance degrades the signal integrity due to reflections
at chip pins because the characteristic impedance of transmission lines on printed
circuit board (PCB) is constant at 50 ${\Omega}$ mostly. To avoid signal integrity
degradation, short-reach interconnects are used for the transmission lines on PCB.
Section II describes issues for power consumption of the DDR3 DRAM interface system.
Section III presents the measured results of the DRAM controller. Section IV presents
the application of this work to the long-reach point-to-point interface and the multi-drop
DRAM interface. Section V concludes this work.
II. POWER CONSUMPTION OF DDR3 DRAM INTERFACE SYSTEM
Among the three issues considered in the Introduction to implementing the DRAM controller
in an ASIC chip, this work focused on reducing power consumption. To implement a low-power
DRAM controller, a double data rate 3 (DDR3) DRAM controller was chosen in this work.
As shown in Fig. 1, the DDR3 DRAM controller consists of a DRAM controller core and a test module. The
DRAM controller core consists of a LINK and three branches; an ADDR/CMD branch, a
DQ/DQS write branch, and a DQ/DQS read branch. Each branch consists of 4:1 serializers
or deserializers and I/O circuits. The LINK performs the master control functions
of the DRAM controller, such as initialization, data read/write, and refresh operations.
To achieve the higher bandwidth, the LINK which consists of complex logic circuits
runs at a 4 times slower clock than the data rate of DQs. In order to compensate the
frequency difference between the LINK and the I/O circuits, 4:1 serializers and deserializers
are added between the LINK and the I/O circuits.
Among the elements of the DRAM controller core (Fig. 1), the I/O circuits for DQ/DQS are the most power-hungry, as shown in Table 1.
The power consumption of I/O circuits is dominated by the current required to drive
the small termination resistance with a large voltage swing, which should be large
enough for the receiver circuit to recover the digital data within a short period
of data rate (one data UI). To avoid reflections of long transmission lines on PCB,
the termination resistance is mostly set to the characteristic impedance of the transmission
line, which is around 50 ${\Omega}$.
However, for short-reach interconnects, increasing the termination resistance to a
value larger than the characteristic impedance of the transmission line does not bring
out serious signal integrity problems. Although increasing the termination resistance
reduces the I/O power, for some combinations of termination resistance at the transmitter
(TX) and receiver (RX), the signal swing at RX falls below the minimum RX voltage
swing required for the error-free recovery of digital data. The minimum RX voltage
swing is defined by the JEDEC standard [7].
The I/O circuits of the DRAM controller in this paper are designed such that the termination
resistance can be changed by the external register control. The TX driver is implemented
by eight parallel tri-state buffer cells (Fig. 2(a)). The resistance of each NMOS and PMOS of the buffer cell is set to 480 ${\Omega}$,
so the TX termination resistance (R$_{\mathrm{TX}}$) ranges from 60 ${\Omega}$ to
480 ${\Omega}$ by the 7-bit thermometer control with the cell 1 turned on in the write
mode. The RX buffer is implemented by a conventional Gunning Transceiver Logic (GTL)
circuit and seven parallel tri-state buffer cells (Fig. 2(b)); the buffer cells work as the RX termination resistance (R$_{\mathrm{RX}}$). The
resistance of each NMOS and PMOS of the buffer cell is set to 480 ${\Omega}$ so that
R$_{\mathrm{RX}}$ ranges from 34 ${\Omega}$ to infinity by the 7-bit thermometer control.
For the commercial DRAM chip, R$_{\mathrm{TX}}$ and R$_{\mathrm{RX}}$ can be changed
by the mode register set (MRS); R$_{\mathrm{TX}}$ is set to 34 or 40 ${\Omega}$ and
R$_{\mathrm{RX}}$ ranges from 20 to 120 ${\Omega}$. However, R$_{\mathrm{TX}}$ and
R$_{\mathrm{RX}}$ of the DRAM chip are set to their default values, 34 ${\Omega}$
and 60 ${\Omega}$, respectively, to focus on the DRAM controller in this work.
The DDR3 DRAM interface adopts the center tap terminated (CTT) logic, as shown in
Fig. 3(a), by following the JEDEC standard; at TX, the transmission line is connected to VDDQ
when D$_{\mathrm{in}}$(t) is ’+1’ and to ground when D$_{\mathrm{in}}$(t) is ’-1’.
The total power is a multiplication of I$_{\mathrm{TX}}$+I$_{\mathrm{RX}}$ and VDDQ
(Eq. (1)); I$_{\mathrm{TX}}$ is the supply current of the TX driver and I$_{\mathrm{RX}}$
is the supply current of the RX buffer. In the AC equivalent circuit of the DDR3 DRAM
interface in Fig. 3(b), the transmission line is a uniformly distributed LC line, where the (V, I) wave
propagates along the line.
The TX supply current I$_{\mathrm{TX}}$(t) is determined by the input data D$_{\mathrm{in}}$(t)
and the incident and reflected current waves at TX, I$_{\mathrm{I,TX}}$ and I$_{\mathrm{R,TX}}$,
as in Eq. (2); D$_{\mathrm{in}}$(t) is either ‘+1’ or ‘-1’ and I$_{\mathrm{TX}}$(t) is 0 when D$_{\mathrm{in}}$(t)
is ‘-1’. The RX supply current I$_{\mathrm{RX}}$(t) is derived as Eq. (3) by applying the Kirchhoff voltage and current laws at the RX node; I$_{\mathrm{I,RX}}$
and I$_{\mathrm{R,RX}}$ is the incident and reflected current waves at RX, respectively.
${\Gamma}$$_{\mathrm{T}}$ and ${\Gamma}$$_{\mathrm{R}}$ are the reflection coefficients
at TX and RX, respectively (Eqs. (4) and (5)).
I$_{\mathrm{I,TX}}$ is determined by the input data D$_{\mathrm{in}}$(t) as in Eq.
(6); the transmission line can be considered as a grounded resistance of Z$_{\mathrm{o}}$
for a fast transition signal D$_{\mathrm{in}}$(t).
I$_{\mathrm{R,TX}}$ is the summation of multiple reflections as in Eq. (7); t$_{\mathrm{f}}$ is the time of flight of the transmission line.
By substituting Eq. (6) and Eq. (7) into Eq. (2), I$_{\mathrm{TX}}$ equation is derived as in Eq. (8).
I$_{\mathrm{I,RX}}$ in Eq. (3) is the first time incident waveform at RX, that is I$_{\mathrm{I.TX}}$ delayed by
t$_{\mathrm{f}}$, as in Eq. (9). All the reflected waveforms are included in I$_{\mathrm{R.RX}}$, as in Eq. (10).
By substituting Eq. (9) and Eq. (10) into Eq. (3), the I$_{\mathrm{RX}}$ equation is derived as in Eq. (11).
To get the average supply power Eq. (1), the long-term time average values of I$_{\mathrm{TX}}$ and I$_{\mathrm{RX}}$ are
derived from Eqs. (8) and (11), respectively. Two cases of D$_{\mathrm{in}}$(t) are considered in this derivation;
one is a random binary sequence of ‘+1’ and ‘-1’ such as a pseudo-random binary sequence
(PRBS) data and the other is a clock signal which repeats the binary sequence of ‘+1’
followed by ‘-1’ indefinitely in time.
In both cases, the long-term time average values of D$_{\mathrm{in}}$(t), D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$)
and D$_{\mathrm{in}}$(t)$^{2}$ at Eq. (8) are 0, 0 and 1, respectively. D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$) is D$_{\mathrm{in}}$(t)
delayed by 2mt$_{\mathrm{f}}$; it arrives at TX after the m-th round trip along the
transmission line. The long-term time average of D$_{\mathrm{in}}$(t)${\cdot}$D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$)
has different values in the two cases. For the case of the random sequence D$_{\mathrm{in}}$(t),
when the m-th reflection arrives within one data period (2mt$_{\mathrm{f}}${\textless}t$_{\mathrm{ui}}$),
D$_{\mathrm{in}}$(t) and D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$) are uncorrelated
during the initial 2mt$_{\mathrm{f}}$ time interval of one t$_{\mathrm{ui}}$, and
they have the same values of either ‘+1’ or ‘-1’ during the remaining t$_{\mathrm{ui}}$-2mt$_{\mathrm{f}}$
time interval, as shown in Fig. 4(a), where D$_{\mathrm{in}}$(t) is assumed to be ‘+1’ during the one t$_{\mathrm{ui}}$
time interval considered. Thus, for 2mt$_{\mathrm{f}}${\textless}t$_{\mathrm{ui}}$,
the long-term time average of D$_{\mathrm{in}}$(t)${\cdot}$D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$)
is (t$_{\mathrm{ui}}$-2mt$_{\mathrm{f}}$)/t$_{\mathrm{ui}}$ as in the first part of
Eq. (12). When the m-th reflection arrives after one data period (2mt$_{\mathrm{f}}$${\geq}$t$_{\mathrm{ui}}$),
D$_{\mathrm{in}}$(t) and D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$) are uncorrelated
during the time interval of one t$_{\mathrm{ui}}$, as shown in Fig. 4(b), the long-term time average of D$_{\mathrm{in}}$(t)${\cdot}$D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$)
is 0 as in the second part of Eq. (12).
By substituting Eq. (12) into Eq. (8), the long-term time average of I$_{\mathrm{TX}}$ for the random binary sequence D$_{\mathrm{in}}$(t)
is given by Eq. (13).
The floor function of Eq. (14) returns the largest integer which is equal to or smaller than the input argument.
For the case of the clock signal D$_{\mathrm{in}}$(t), which is ‘+1’ during the time
interval of one t$_{\mathrm{ui}}$ and ‘-1’ during the following t$_{\mathrm{ui}}$,
the long-term time average of D$_{\mathrm{in}}$(t)${\cdot}$D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$)
can be calculated in two cases; in the first case (Fig. 5(a)), the rising edge of the reflected clock signal D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$)
arrives at TX while D$_{\mathrm{in}}$(t) is ‘+1’, and in the second case (Fig. 5(b)), the rising edge of D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$) arrives at TX while
D$_{\mathrm{in}}$(t) is ‘-1’. A normalized variable x, as defined in Eq. (15), ranges from 0 to 0.5 for the first case and it ranges from 0.5 to 1.0 for the second
case. The time-average of D$_{\mathrm{in}}$(t)${\cdot}$D$_{\mathrm{in}}$(t-2mt$_{\mathrm{f}}$)
can be derived as f(x) shown in Eq. (16) for the case of the clock signal D$_{\mathrm{in}}$(t).
Substitution of Eq. (16) into Eq. (8) yields the long-term time average of I$_{\mathrm{TX}}$ for the clock signal D$_{\mathrm{in}}$(t)
as Eq. (17).
The long-term time average of I$_{\mathrm{RX}}$ is derived as Eq. (18) independently of D$_{\mathrm{in}}$(t), because the long-term time average values
of D$_{\mathrm{in}}$(t-t$_{\mathrm{f}}$) and D$_{\mathrm{in}}$(t-(2m+1)t$_{\mathrm{f}}$)
in Eq. (11) are all 0 for both the random binary sequence and the clock signal D$_{\mathrm{in}}$(t).
Fig. 6 shows the long-term time average of the supply current I$_{\mathrm{TX}}$+I$_{\mathrm{RX}}$
versus the length of the transmission line; a lossless transmission line is assumed.
For a given length of transmission line, the supply current is reduced by increasing
either R$_{\mathrm{TX}}$ or R$_{\mathrm{RX}}$. The calculation using Eqs. (13), (17) and (18) yields an absolute error of less than 0.8% from the SPICE simulation; t$_{\mathrm{ui}}$
is 0.5 ns and t$_{\mathrm{f}}$ is calculated using the propagation velocity along
the transmission line of 1.711*10$^{10}$ cm/s assuming a microstrip transmission line
on FR-4 PCB.
If t$_{\mathrm{f}}$=0, that is, no transmission line is used, the long-term time average
I$_{\mathrm{TX}}$ equations Eqs. (13) and (17) should be reduced to the average DC current equation 0.25VDDQ/(R$_{\mathrm{TX}}$+R$_{\mathrm{RX}}$).
Because t$_{\mathrm{f}}$=0 gives (t$_{\mathrm{ui}}$-2mt$_{\mathrm{f}}$)/t$_{\mathrm{ui}}$=1,
M=infinity, x=0, f(x)=1, Eqs. (13) and (17) result in the same equation Eq. (19), which agrees with the DC current equation. This verifies the validity of Eqs. (13) and (17) for the DC case.
Eq. (19) corresponds to the minimum value of Eqs. (13) and (17) for all t$_{\mathrm{f}}$ if ${\Gamma}$$_{\mathrm{T}}$${\geq}$0 and ${\Gamma}$$_{\mathrm{R}}$${\geq}$0.
In Fig. 6, we can observe the periodic change of I$_{\mathrm{TX}}$+I$_{\mathrm{RX}}$ w.r.t.
the length of the transmission line for the clock signal D$_{\mathrm{in}}$(t); I$_{\mathrm{TX}}$+I$_{\mathrm{RX}}$
is minimized at 2t$_{\mathrm{f}}$=2nt$_{\mathrm{ui}}$ and maximized at 2t$_{\mathrm{f}}$=(2n+1)t$_{\mathrm{ui}}$;
n is an integer. This is due to the time synchronization of the incident and reflected
current waves at TX; they are synchronized in the same phase at 2t$_{\mathrm{f}}$=2nt$_{\mathrm{ui}}$
(Fig. 7(a)) and in the alternately opposite phase at 2t$_{\mathrm{f}}$=(2n+1)t$_{\mathrm{ui}}$
(Fig. 7(b)). Both R$_{\mathrm{TX}}$ and R$_{\mathrm{RX}}$ are assumed to be larger than Z$_{\mathrm{o}}$.
Because I$_{\mathrm{TX}}$ is the difference between the incident and reflected current
waves as in Eq. (3), the same phase synchronization gives the minimum I$_{\mathrm{TX}}$ as in Eq. (19) and the alternately opposite phase synchronization gives the maximum I$_{\mathrm{TX}}$
as in Eq. (20).
Although increasing R$_{\mathrm{TX}}$ or R$_{\mathrm{RX}}$ reduces the power consumption
of the DRAM interface (Fig. 3) as dictated by Eqs. (13), (17) and (18), some combinations of R$_{\mathrm{TX}}$ or R$_{\mathrm{RX}}$ cannot meet the minimum
RX voltage swing which is required to retrieve the correct digital data at RX within
t$_{\mathrm{ui}}$; it is defined to be V$_{\mathrm{ref}}$ ${\pm}$ 0.1VDDQ for DDR3
DRAM chips by the JEDEC standard with VDDQ=1.5 V and V$_{\mathrm{ref}}$=0.75 V. The
RX voltage swing is determined by the transmission line effects such as reflections
as well as the termination resistors (R$_{\mathrm{TX}}$, R$_{\mathrm{RX}}$). With
R$_{\mathrm{TX}}$=34 ${\Omega}$ and R$_{\mathrm{RX}}$=60 ${\Omega}$ for the DDR3 DRAM
chip, the R$_{\mathrm{TX}}$ of the DRAM controller cannot exceed 240 ${\Omega}$ and
R$_{\mathrm{RX}}$ can be increased indefinitely to maintain the minimum DC RX voltage
swing, as can be seen in Table 2.
To find the reduction of the RX voltage swing by the reflections due to the unmatched
R$_{\mathrm{TX}}$ and R$_{\mathrm{RX}}$, chip package and vias, SPICE simulation is
performed for the circuit model of the DDR3 DRAM interface (Fig. 8). The circuit model includes the TQFP176 package [12] for the DRAM controller, the pi via model [13], the IBIS model of the commercial DDR3 DRAM chip [14], the RLGC parameters of a microstrip line extracted from the measured S-parameters.
Fig. 9 shows the eye diagram of the simulated RX voltage with D$_{\mathrm{in}}$(t)=2.133
Gbps PRBS-15 and the length of the transmission line 5 cm. The controller R$_{\mathrm{TX}}$=240
${\Omega}$ cannot meet the RX eye mask requirement of 300 mV and 280 ps (Fig. 9(a)), while the controller R$_{\mathrm{TX}}$=160 ${\Omega}$ satisfies the requirement
(Fig. 9(b)). The controller R$_{\mathrm{RX}}$=infinity satisfies the requirement (Fig. 9(c)).
From the RX voltage swing from SPICE simulation w.r.t. the length of the transmission
line for different values of controller R$_{\mathrm{TX}}$ and R$_{\mathrm{RX}}$ shown
in Fig. 10, we can increase the length of the transmission line up to 6~cm at write mode with
the controller R$_{\mathrm{TX}}$=160 ${\Omega}$ with DRAM R$_{\mathrm{RX}}$=60 ${\Omega}$.
Also, we can use a long transmission line and a large controller R$_{\mathrm{RX}}$
at read mode with DRAM R$_{\mathrm{TX}}$=34 ${\Omega}$.
Table 1. Power consumption of the DRAM interface including DRAM and controller (HSPICE simulation for I/O circuits and IC compiler reports for logic circuits, 60 ${\Omega}$ termination for write and 34 ${\Omega}$ termination for read)
DQ/DQS circuits (DRAM)
|
177 mW
|
DQ/DQS circuits (controller)
|
239 mW
|
ADDR/CMD drivers & logic (DRAM)
|
99 mW
|
ADDR/CMD drivers & logic (controller)
|
99 mW
|
Total power
|
614 mW
|
Table 2. DC RX voltage level and swing
RX voltage level, Din='-1'
|
RX voltage level, Din='+1'
|
RX voltage swing
|
$\frac{\text{VDDQ}\cdot \mathrm{R}_{\mathrm{TX}}}{2\left(\mathrm{R}_{\mathrm{TX}}+\mathrm{R}_{\mathrm{RX}}\right)}$
|
$\frac{\text{VDDQ}\cdot \left(\mathrm{R}_{\mathrm{TX}}+2\mathrm{R}_{\mathrm{RX}}\right)}{2\left(\mathrm{R}_{\mathrm{TX}}+\mathrm{R}_{\mathrm{RX}}\right)}$
|
$\frac{\text{VDDQ}\cdot \mathrm{R}_{\mathrm{RX}}}{\mathrm{R}_{\mathrm{TX}}+\mathrm{R}_{\mathrm{RX}}}$
|
Fig. 1. Block diagram of DDR3 DRAM controller ASIC connected to an external DDR3 DRAM chip.
Fig. 2. I/O circuits of DDR3 DRAM controller: (a) TX driver; (b) RX buffer.
Fig. 3. I/O circuits of DDR3 DRAM controller: (a) TX driver; (b) RX buffer.
Fig. 4. Waveforms for random binary sequence D$_{\mathrm{in}}$(t): (a) 2mt$_{\mathrm{f}}${\textless}t$_{\mathrm{ui}}$; (b) 2mt$_{\mathrm{f}}$${\geq}$t$_{\mathrm{ui}}$.
Fig. 5. Waveforms for clock signal D$_{\mathrm{in}}$(t): (a) x{\textless}0.5; (b) x${\geq}$0.5; x is the normalized t$_{\mathrm{f}}$ as in Eq. (15).
Fig. 6. Long-term time average of I$_{\mathrm{TX}}$+I$_{\mathrm{RX}}$ versus the length of transmission line for calculation (solid line) and SPICE simulation (symbol): (a) PRBS-7 D$_{\mathrm{in}}$(t); (b) clock D$_{\mathrm{in}}$(t).
Fig. 7. Waveforms of the incident current wave, reflected current waves and I$_{\mathrm{TX}}$ for clock signal D$_{\mathrm{in}}$(t) while D$_{\mathrm{in}}$(t)=‘+1’: (a) 2t$_{\mathrm{f}}$=2nt$_{\mathrm{ui}}$; (b) 2t$_{\mathrm{f}}$=(2n+1)t$_{\mathrm{ui}}$.
Fig. 8. Circuit model of DDR3 DRAM interface with PCB routing and chip package models: (a) write mode; (b) read mode.
Fig. 9. Eye diagrams of DDR3 DRAM interface for 2.133 Gbps PRBS-15 input: (a) write mode, controller R$_{\mathrm{TX}}$=240 ${\Omega}$, DRAM R$_{\mathrm{RX}}$=60 ${\Omega}$; (b) write mode, controller R$_{\mathrm{TX}}$=160 ${\Omega}$, DRAM R$_{\mathrm{RX}}$=60 ${\Omega}$; (c) read mode, controller R$_{\mathrm{RX}}$=infinity(open), DRAM R$_{\mathrm{TX}}$=34 ${\Omega}$.
Fig. 10. RX voltage swing of the DRAM interface with the length of transmission line for 2.133 Gbps PRBS-15 input: (a) write mode for 3 R$_{\mathrm{TX}}$ of the controller, DRAM R$_{\mathrm{RX}}$=60 ${\Omega}$; (b) read mode for 3 R$_{\mathrm{RX}}$ of the controller, DRAM R$_{\mathrm{TX}}$=34 ${\Omega}$.