This disclosure relates generally to memory arrays used in data processing, such as multiply-accumulate operations. Compute-in-memory or in-memory computing systems store information in the main random-access memory (RAM) of computers and perform calculations at memory cell level, rather than moving large quantities of data between the main RAM and data store for each computation step. Because stored data is accessed much more quickly when it is stored in RAM, compute-in-memory allows data to be analyzed in real time, enabling faster reporting and decision-making in business and machine learning applications. Effort are ongoing to improve the performance of compute-in-memory systems.
Aspects of the present disclosure are best understood from the following detailed description when read with the accompanying figures. It is noted that, in accordance with the standard practice in the industry, various features are not drawn to scale. In fact, the dimensions of the various features may be arbitrarily increased or reduced for clarity of discussion.
The following disclosure provides many different embodiments, or examples, for implementing different features of the provided subject matter. Specific examples of components and arrangements are described below to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting. For example, the formation of a first feature over or on a second feature in the description that follows may include embodiments in which the first and second features are formed in direct contact, and may also include embodiments in which additional features may be formed between the first and second features, such that the first and second features may not be in direct contact. In addition, the present disclosure may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.
Specific examples shown in this disclosure relate to computing-in-memory. An example of applications of computing-in-memory is multiply-accumulate operations, in which an input array of numbers are multiplied (weighted) by the respective elements in another array (e.g., column) of numbers (weights), and the products are added together (accumulated) to produce an output sum. This is mathematically similar to a dot product (or scalar product) of two vectors, in which procedure the components of two vectors are pair-wise multiplied with each other, and the products of the component pairs are summed. In certain artificial intelligence (AI) systems, such as artificial neural networks, an array of numbers can be weighted by multiple columns of weights. The weighting by each column produces a respective output sum. An output array of sums thus is produced from an input array of numbers by the weights in a matrix of multiple columns.
A common type of integrated circuit memory is a static random-access memory (SRAM) device. A typical SRAM memory device has an array of memory cells. In some examples, each memory cell uses six transistors (6T) connected between an upper reference potential and a lower reference potential (e.g., ground) such that one of two storage nodes can be occupied by the information to be stored, with the complementary information stored at the other storage node. Each bit in the SRAM cell is stored on four of the transistors, which form two cross-coupled inverters. The other two transistors are connected to the memory cell word line (WL) to control access to the memory cell during read and write operations by selectively connecting the cell to its bit lines (BLs). When the word line is enabled, a sense amplifier connected to the bit lines senses and outputs stored information. Input/output (I/O) circuitry connected to the bit lines are often used when processing memory cell data. Both bit lines can be low/high when multiple WLs are activated and bit-cells are storing opposite values initially.
In multi-bit applications, such as compute-in-memory, the stability of a 6T bit-cell can be degraded when multiple word lines are activated at the same time. When multiple word lines are activated at the same time, both bit line voltages will be pulled low. This can cause an upset for the stability of the bit cell and cause its state to be flipped. Additionally, using logic-rule based SRAM bit-cells has significant area overhead, due to, among other things, storage needed for intermediate calculations. Still further, binary input/weight/output using known memory arrangements can be too simplistic for general usage of compute-in-memory, as many problems to be solved by algorithms used in computer-in-memory require multi-bit computation steps. Certain embodiments disclosed in this disclosure provide multi-bit compute-in-memory, with direct results without requiring intermediate storage space, and without upsetting the stability of each cell.
In accordance with some aspects of the present disclosure, a compute-in-memory (CIM) system includes a memory array memory array in which each memory cell has mutually isolated read bit-line (RBL), through which the store information can be read, and write bit-line (WBL), through which information can be written to the cell. For example, an 8T SRAM cells, which adds to a 6T SRAM a 2T read port connected to a read word line (RWL) and a RBL. Because the RBL of the 8T bit cell has is decoupled from the 6T memory cell, multiple RWLs turning on simultaneously does not upset the storage node voltage. Some disclosed embodiments provide a CIM system that has an array of 8T SRAM cells including a plurality of RWLs and RBLs.
In according to certain aspects of the present disclosure, a CIM system having a multi-bit input can be realized with multiple RWL pulses. For example, in some embodiments, an input signal in multiply-accumulate operations can be realized by a number of RWL pulses, the number being proportional to the input. In some examples, a 4-bit input can be used, but other bit widths are within the scope of the disclosure. For example, an input of 0 is represented by 0 (00002) RWL pulses, an input of 310 (00112) is represented by 3 RWL pulses, an input of 1510 (11112) is represented by 15 RWL pulses, and so on.
In some embodiments, the input signals can be multiplied by multi-bit (e.g., four-bit) weights (i.e., weight values) arranged in a column. Accumulation of multi-bit-weighted inputs can be realized by charging a common RBL from all cells in a column corresponding to each bit of the multi-bit weight; the voltage on each RBL thus is indicative of the sum of the currents from each cell connected to the RBL and is thus indicative of the sum of the inputs, each weighted by the binary weight associated with the column. A multiply-accumulate function is thus performed on the RBLs, and the RBL voltage is proportional to a bit-wise multiplication of weight bit with multi-bit inputs. Charge sharing among RBLs is then performed for each column of multi-bit weights, with binary-weighted capacitors, i.e., capacitors sized according to the respective positions of significance in the multi-bit weights. Accordingly, the most significant bits (MSB) of weight contribute more to the final output than the least significant bits (LSB) of the weight. The charge sharing therefore produces an analog voltage that reflects the correct significance of each RBL. For example, with a column of four-bit weights, the contribution to the final voltage from most MSB would be eight (23) times the contribution from the LSB; the contribution from the second MSB would be four (22) times the contribution from the LSB; and the contribution from the third MSB (or second LSB) would be two (21) times the contribution from the LSB.
In certain further embodiments, an analog-to-digital converter (ADC), such as a Flash ADC, is used in some examples to convert a voltage on the RBLs (after binary-weighted charge sharing such as noted above) to a multi-bit digital output. In some embodiments, for an n-bit output, 2n−1 comparators are sued for ADC implementation. For example, for a 4-bit output example, 15 comparators are used for the flash ADC implementation. Each comparator in some embodiments has its own input capacitor. These input capacitors may be used as the above-mentioned binary-weighted capacitors for charge sharing. The number of input capacitors each RBL is connected to is related to (e.g., proportional to) the place value of the output bit associated with the RBL in certain embodiments. For example, for a 4-bit output, the RBL for the MSB is connected to 8 (23) input capacitors; the RBL for the LSB is connected to 1 (20) input capacitor. The total capacitance connected to each RBL is thus in proportion to the place value corresponding to the RBL. Other bit-width outputs are within the scope of the disclosure.
Referring to
For some applications, a model system can be a multiply-accumulate system, which processes a set of inputs by multiplying each input with a value, sometimes called a “weight,” and sum (accumulate) the products together. The system can include a two-dimensional array of elements arranged in rows and columns, each of the elements storing a weight, and capable of receiving an input and generating an output that is the arithmetic product of the input and the stored weight. The model system can have each input supplied to an entire row of elements and the outputs of each column of the elements added together.
For example, the system (100) shown in
It is evident from this table that the output is the product of the input and weight.
Furthermore, because the cells (110) in the same column share the same RBL, the current on the RBL is the sum of the current to the cells (110) connected to it. Therefore, the signal on each RBL represents the sum of binary products of the inputs (RWLs) and the respective stored weights.
Referring to
Given the capacitance on each RBL (9*Cu in this example), the voltage drop (assuming the capacitors are precharged) at each node N0, N1, N2 or N3 (
Next, referring further to
ΔV=Σj2jIj,
where Ij is the current for the jth RBL and is proportional to the sum of binary products of the inputs (RWLs) and the respective stored weights for the jth RBL. ΔV, therefore is proportional to the sum of products between the inputs and the respective multi-bit weights store in the cells [110].
Finally, with additional reference to
To explain the above-outlined system and its operation in more detail, a compute-in-memory system in some embodiments includes a memory array (100), which includes rows and columns (which can be either physical or logical rows and columns) of memory cells (110), as well as other components, such as a digital input interface (not shown in
Each memory cell (110) in this example includes a 6T memory cell (120) and a read port (150). The 6T memory cell (120) includes a first inverter (126), made of a p-type metal-oxide-semiconductor (MOS) field-effect transistor (PMOS) (122) and an n-type MOS field-effect transistor (NMOS) connected in series (i.e., with the source-drain current paths in series) between a high reference voltage (such as VDD) and low reference voltage (such as ground); a second inverter (136), made of a PMOS (132) and an NMOS (134) connected in series between the high reference voltage (such as VDD) and low reference voltage (such as ground); and two write access transistors (142, 144), which in this example are NMOS's. The inverters (126, 136) are reverse-coupled, i.e., with the output (Q, QB)) (i.e., the junction between source/drain current paths) of one coupled to the input (i.e., the gates) (QB, Q) of the other; the write access transistors (142, 144) each have its source/drain current path connected between a respective junction of the reversed coupled inverters (126, 136) and respective write bit-line (WBL (170), WBLB (180)), and its gate connected to a write word-line (WWL) (160).
Each read port (150) in this example includes a read transistor (152) and a read access transistor (154) in serial connection with each other and connected between the low reference voltage and a data output line, sometimes referred to as a read bit-line (RBL). The read transistor (152) in this example is an NMOS, and its gate is connected to inverted output (QB) of the 6T memory cell (120); the read access transistor (154) in this example is an NMOS, and its gate is connected to a read word-line (RWL). Other types of transistors and connections can be used. For example, PMOS's can be used for both or either of the read transistor (152) and read access transistor (154); the gate of the read transistor (152) can be connected to the non-inverted output (Q) of the 6T memory cell (120).
In operation, to write a bit a memory cell (110), a data bit (1 or 0) (e.g., a voltage corresponding to 1 or 0) is applied to the WBL and its inverse to WBLB. A write signal (e.g., 1) is applied to the write access transistors (142, 144) to make the transistors conducting, thereby storing the data bit at output (Q) of the 6T memory cell (120) and the inverse of the data bit at (QB). The write access transistors (142, 144) can be turned off thereafter, and the value at Q, and the inverse at QB, are maintained. To read the stored data bit, the write access transistors (142, 144) are turned off (WL=0), and the read access transistor (154) is turned on (conducting) by a read signal applied to the RWL. A cell current, Icell, corresponding to the voltage at QB (or Q), which in turn signifies the stored value (1 or 0) in the 6T memory cell (120), is thus generated in the RBL and sensed by the circuitry in the output interface (not shown in
Because the RBL is isolated from output Q or QB of the inverters (126, 136) (i.e., the voltage and current on or in the RBL has substantially no effect at Q or QB) by the read transistor (152) in each read port (150), and/or because the write access transistors (142, 144) are turned off (WL=0), multiple RWL's can be activated (i.e., multiple read access transistors (154) made turned on) simultaneously without upsetting the voltage at Q or QB.
According to some embodiments, as shown in
The memory cells (110) in the array (100) in some embodiments are of identical construction. In other embodiments, the memory cells (110) in the array (100) can be different from each other. For example, the size ratios between the transistors (152, 154) in the respective read ports (150) can be different from memory cell to memory cell, such that the currents generated by the same RWL signal are different.
The CIM system (200) in this example further includes an input interface (210), which in this example includes an array of digital counters (212) and a corresponding array of drivers (214). In this example, there are 64 4-bit counters (212), one for each row of the 64×64 memory cell array (100); each counter (212) outputs a number of pulses per counting cycle corresponding to the number (in this case a 4-bit binary number) at the counter input. For example, an input of 0 (00002) generates 0 pulses, an input of 310 (00112) generates 3 RWL pulses, an input of 1510 (11112) generates 15 RWL pulses, and so on. A driver (214) corresponding to each counter (212) drives the corresponding RWL (190[j] (j=0 through 63)) according to the output pulses from the counter. Thus a train of RWL pules, the number of which per counting cycle is indicative of the digital number at the input of the respective counter (212) is applied to the corresponding RWL (156[i] (i=0 through 63)).
The CIM system (200) in some embodiments further includes a read/write (RW) interface (216) connected to the memory array (100) for conventional reading and writing operations associated with memory arrays.
The CIM system (200) in some embodiments also includes an output interface (220), which in some examples includes a compensation module (222) connected to the memory array (100), and computation module (224) connected to the compensation module (222). As described below in more detail, the compensation module serves to form, with the computation module (224), a uniform environment, i.c., the same total capacitance, for pre-charging and sampling of the RBL's; the computation module (224) serves to compute quantities indicative of the signal values on the RBL's or certain combinations thereof. For example, as described in more detail below, in some embodiments, the computation module (224) is adapted to compute weighted sums or weighted averages of several RBL's. This is done in some embodiments through charge sharing among capacitors sized according to the relative positions of significance (most-significant bit (MSB) to least-significant-bit (LSB)) of the respective RBL's in a binary number. For example, the relative sizes of the capacitors in some embodiments are 23:22:21:20 from MSB to LSB. As a result, the amplitude of the resultant signals correspond to sums of multi-bit input signals weighted by multi-bit weights.
In some embodiments, as shown for a four-bit-wide segment (230) of the CIM system (200) in
The computation module (224) includes a set of integrators for integrating the current on each RBL. In some embodiments, integrators include computation capacitors Cm[j] (j=0 through 3 for each four-bit-wide segment (230)), each associated with a respective RBL (190[j] (j=0 through 3) and corresponding compensation capacitor Cn[j]). The computation capacitors in some embodiments are used in combination with the compensation capacitors to provide a capacitance to the respective RBLs to build up a voltage that is indicative of the sum of the weighted inputs for the RBLs. The computation capacitors in some embodiments, as explained briefly above, are paired with respective compensation capacitors to present the same capacitance to each RBL during certain steps of the computation process. As explained further below, the computation capacitors are sized relative to each other in some embodiments to attribute a significance to the respective RBLs. A pair of switch devices, SH and S1, such as any switching transistors, are associated with each computation capacitor Cm[j], with SH connecting the computation capacitor Cm[j] to the respective RBL (190[j]) via S0B, and S1 connecting, via SH, the computation capacitor Cm[j] to an analog output (228). Each computation capacitor Cm[j] is connected at one end to the analog output (228) through respective SH and S1, and at the other end to a voltage reference, such as ground.
In some embodiments, as shown in
Thus, the array (100) of memory cells (110) in the example CIM system (200) shown in
In some embodiments, the capacitance of the computation capacitors Cm[j] are chosen according to their respective relative positions in the computation module, i.e., the index j. For example, in the embodiment shown in
In some embodiments, the capacitance of the compensation capacitors Cn[j] are chosen according to their respective relative positions in the computation module, i.e., the index j. In some embodiments, the capacitance of the compensation capacitors Cn[j] are chosen such that Cn[j]+Cm[j]=constant, i.e., the RBLs are presented with the same (constant capacitance) when each pair of compensation and computation capacitors are connected in parallel, and Cn[j] is the difference between a fixed total capacitance and the respective computation capacitance Cm[j]. For example, in the embodiment shown in
In some embodiments, the output interface (220) further includes a sense amplifier (226) for each RBL (190) for boosting the analog signal from the RBL (190). The output interface (220) in some embodiments further includes an analog-to-digital converter (ADC) (270) for each subset of RBL's associates with a column of multi-bit weights stored in the respective subsets (260) of memory cells (110). In some embodiments, as shown in
In some embodiments, the comparators (272) each include an input capacitor, and those input capacitors can be utilized as the computation capacitors, Cm. For example, in the embodiment shown in
In some embodiments, in-memory computation, such as that of weighted sum, can be performed using the CIM system disclosed in this disclosure. More specifically, a sum of inputs (e.g., 64 inputs), Xi, can be each weighted by a multi-bit (e.g., four-bit) weight, (Wi)k, and the weighted inputs Xi(Wi)k can be summed together to generate an output Sk, that is the weighted sum for the k-th column of multi-bit weights. That is,
As described above, in some embodiments, the digital inputs to the CIM system (200) can be represented by, or converted to, trains of pulses, with the number of pulses per counting cycle at each RWL being indicative of the amplitude of the input. Furthermore, the RWL's can be activated simultaneously because the RBL's are decoupled from the 6T memory cells (120), the RWL's can be activated simultaneously. Further as described above, according to some embodiments, a multi-bit weight, such as a four-bit weight, Wi=(Wi[3]Wi[2]Wi[1]Wi[0])2, can be stored in a subset (260[i]) of a row (190[i]) of memory cells (110), as shown in
First (510), a set of multi-bit weights (e.g., Wi=(Wi[3]Wi[2]Wi[1]Wi[0])2) are stored in an array of memory cells, each having a memory unit (such as a 6T SRAM cell) adapted to store a signal at a node and a read port having a read-enable input line (such as RWL) and an output line (such as RBL), the read port adapted to, upon an activation signal at the read-enable input, generate at the output a signal indicative of the signal stored at the node in the memory unit and isolate the output line from the node.
Next (520), a set of pulsed signals, each indicative of a respective input number, are each applied to the read-enable inputs of a set of memory cells storing a respective multi-bit weight to generate a set of signals at the output lines of the respective memory cells, the set of output signals being indicative of an operation (e.g., multiplication) on the pulsed signals by the stored multi-bit weight.
Next (530), a combined read-port output (e.g., combined current) from the read output lines of the memory cells sharing each output line is measured (e.g., by RBL sampling, described in detail below) and given a significance factor corresponding to the significance (i.e., the place value) of the weight bit (e.g., j for Wi[j]) associated with the output line. For example, the MSB of a four-bit weight has a place value of 8 (i.e., 23); the significance factor can be the place value itself, or some multiple of the place value. The significance factor can be given to each RBL by the use of a relative size of the corresponding computation capacitor, as described above.
Next (540), the combined read-port outputs from the respective read output lines are combined (e.g., by charge sharing, as described in detail below) in proportion to the respective significance factor to generate a computation output signal.
Next (550), the computation output signal is converted to a digital output (e.g., by a 15-comparator analog-to-digital converter (ADC)).
As shown in
First, during a precharge period (310), a precharge signal, PCH, is applied to each RBL[j] and the parallel combination of computation capacitor Cm[j] and compensation capacitor Cn[j], i.e., with S0A, S0B and SH conducting (ON) and S1 non-conducting (OFF). As each combination has the same capacitance, i.e., 9×Cu, all combinations is charged to the same total charge, and the voltages at all four nodes N3, N2, N1 and N0 rise to the same level, VPCH. Next, during a RBL sampling period (320) (see
Next, during a charge sharing period (330) (see
where Q[i] is the charge stored in the j-th computation capacitor Cm[j].
Because the capacitance of Cm[j] is 2jCu/9Cu=of 2j/9 of the total capacitance (9Cu) on the j-th RBL, each computation capacitor Cm[j] takes up 2j/9 of the total charge stored on each RBL from the precharge step. Cm[3] thus has eight times the charge Cm[0] does at the end of the precharge period, Cm[2] four times, and Cm[1] twice. For the same reason, during the RBL sampling period, Cm[3] loses eight times the charge Cm[0] does for the same input and same weight bit value, Cm[2] four times, and Cm[1] twice. Thus, at the end of the charge sharing period, the contribution to the total charge, ΣjQ[j], from Cm[3] is eight times that from Cm[0], Cm[2] four times, and Cm[1] twice. The voltage, Vout, or the voltage drop, ΔV=VPCH-Vout, therefore represents a binary-weighted sum in which each RBL is assigned a weight proportional to the RBL's position of significance in the binary weight, Wi=(Wi[3]Wi[2]Wi[1]Wi[0])2, or more generally, Wi=( . . . Wi[j] . . . Wi[2]Wi[1]Wi[0])2. For example, in the embodiment shown in
Next, during a ADC evaluation period (an SAE signal “ON” to enable the ADC (226) to convert the voltage on the RBL's (190), i.e., at N3, N2, N1, and N0, after the above-described charge sharing to a digital output signal, in this example a four-digit binary number (00002 through 11112) corresponding to the voltage. An in-memory computation involving multiply-and-accumulation, with multi-bit inputs and multi-bit weight, is thus accomplished.
Because the RBL's are decoupled from the respective 6T memory cells, multiple RWL's can be activated simultaneously to apply the weights stored in the memory cells (110) without upsetting the stored state of any memory cell. Computation speed is thus improved as compared the situation in which the RWL's must be applied one at a time.
Thus, in accordance with some disclosed embodiments, a computing device includes a memory array having a set of memory cells grouped in rows and columns of memory cells, each of the memory cells having a memory unit adapted to store data, and a read port having an read-enable input and an output; read-enable lines, each connected to, and adapted to transmit an input signal to, the read-enable inputs of the read ports of a respective row of memory cells; data-output lines, each connected to the outputs of the read ports of a respective column of memory cells; an output interface having a computation module that includes a set of capacitors, each being connectable to a respective one of the data-output lines and having a capacitance, at least two of the of capacitors having different capacitance from each other, the output interface being configured to permit the capacitors to share charge stored on them.
In accordance with some disclosed embodiments, a method of computing includes storing a plurality of multi-bit weights in a memory array having memory cells organized in rows and columns and each having a memory unit adapted to store a signal at a node and a read port having a read-enable input and an output, the read port adapted to, upon an activation signal at the read-enable input, generate at the output a signal indicative of the signal stored at the node in the memory unit and isolate the output from the node, the memory array further having a plurality of read-enable lines, each connected to the read-enable inputs of a row of the memory cells, where storing each of the plurality of multi-bit weights includes storing the multi-bit weight in a row of memory cells sharing a respective one of the read-enable lines, the memory array further having data-output lines, each connected to the outputs of the read ports of a column of the memory cells; applying trains of pulsed signals to the respective read-enable lines to generate an output signal on each of the data-output lines; weighting the combined output signal by a significance factor, at least two of the significance factors being different from each other; combining the weighted output signals to generate an analog output; and converting the analog output to a digital output.
In accordance with some disclosed embodiments, a computing method includes storing multi-bit weights in a memory array having a plurality of memory cells organized in rows and columns and each having a memory unit adapted to store a signal at a node and a read port having a read-enable input and an output, the read port adapted to, upon an activation signal at the read-enable input, generate at the output a signal indicative of the signal stored at the node in the memory unit and isolate the output from the node; simultaneously multiplying an input signal by each bit of each of the multi-bit weights to generate output signals at the output of each of the read ports; summing the output signals at the outputs of the read ports of the memory cells in each column; weighting each of the sums of the output signals at the outputs of the read ports of the memory cells in each column by a different significance factor to generate a respective weighted sum; and combining the weighted sums to generate an analog output signal.
The foregoing outlines features of several embodiments so that those skilled in the art may better understand the aspects of the present disclosure. Those skilled in the art should appreciate that they may readily use the present disclosure as a basis for designing or modifying other processes and structures for carrying out the same purposes and/or achieving the same advantages of the embodiments introduced herein. Those skilled in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the present disclosure, and that they may make various changes, substitutions, and alterations herein without departing from the spirit and scope of the present disclosure.
This application is a continuation of U.S. application Ser. No. 17/734,701, filed May 2, 2022, which is a continuation of U.S. application Ser. No. 17/034,701, filed Sep. 28, 2020, now U.S. Pat. No. 11,322, 195, which application claims the benefit of U.S. Provisional Application No. 62/941,330 titled “COMPUTER IN MEMORY SYSTEM” and filed Nov. 27, 2019, the disclosure of which are hereby incorporated by reference in their entirety.
Number | Date | Country | |
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62941330 | Nov 2019 | US |
Number | Date | Country | |
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Parent | 17734701 | May 2022 | US |
Child | 18781286 | US | |
Parent | 17034701 | Sep 2020 | US |
Child | 17734701 | US |