Silicon Brain

Abstract

To provide an information storage system which simulates a neural network on a silicon chip without using a bit.SOLUTION: A neural network has: a plurality of islands periodically disposed in a first axis direction and a second axis direction on a surface of a semiconductor device; a first link and a second link disposed between two islands adjacent to each other in the first direction and the second direction among the plurality of islands; and a first word line in a third axis direction; and a second word line in a fourth axis direction. Each of the plurality of islands has a diffusion layer formed on the surface of the semiconductor device. The first link is a first selection gate for bridging the two islands adjacent to each other in the first direction among the plurality of islands. The second link is a second selection gate for bridging the two islands adjacent to each other in the second direction among the plurality of islands. The first selection gate and the second selection gate have respective selection gate contacts. The selection gate contact is selected by the first word line and the second word line.SELECTED DRAWING: Figure 7

Description

[Technical Field]

[0001] The present invention relates to a technique for integrating a neural network on a silicon chip (IC chip). [Background technology]

[0002] In conventional semiconductor computing, a memory device (memory) and a processing unit (e.g., a CPU) work together. A memory device (semiconductor memory) consists of a collection (array, cell array, memory cell array, or memory element array) of memory elements called memory cells (memory elements, bit cells, or simply cells). Each element consists of at least a source, a drain, and a gate (or control gate). The source and drain can each be connected to a bit line. The gate is each connected to a word line. This connection is typically made through a contact (terminal), such as a word line contact (terminal) or a bit line contact (terminal). When a collection of such elements is distributed on a two-dimensional plane, each memory element is accessed via word lines (WL) and bit lines (BL) arranged in the mutually perpendicular X and Y directions of the two-dimensional plane. For example, the address of a memory element located at the intersection of the Ath word line and the Bth bit line is (A, B). This is called the address of the memory element. Here, A is specifically referred to as the address on the X axis (X address). B is specifically called the address on the Y axis (Y address).

[0003] For a long time, the mainstream of semiconductor memory technology development was to integrate as many memory elements as possible on the surface of a silicon wafer using semiconductor manufacturing processes in accordance with Moore's Law (see Non-Patent Document 1). However, in recent years (since 2015), it has become difficult to increase the integration density of memory elements on a two-dimensional plane, and the method of placing memory elements in three-dimensional space has become mainstream, even at the mass-produced level. In this case, addresses can be represented as (A, B, C), where C is the address on the Z axis (Z address), which is perpendicular to the XY plane.

[0004] However, whether it is two-dimensional or three-dimensional, the current method of recording information in semiconductor memory devices is based on memory elements, and when each memory element (cell) has two values, 0 and 1, it is said that one cell has a memory capacity (amount of information that can be stored) of 1 bit. If there are two such memory elements, the memory capacity is said to be 2 bits. In this case, there are four possible combinations of 0 and 1: (00), (01), (10), and (11). In this case, the number can be calculated by raising to the power of 2. If a cell array is made up of N memory elements, the memory capacity of the cell array is N bits. In this case, the number can be calculated by raising to the power of 2N.

[0005] Therefore, the amount of information (number of bits) in conventional semiconductor devices is expressed as the number of cases in logarithms where the low is 2. Even when so-called multi-value technology is used, the low of the logarithm simply becomes 4 or 8, and such logarithms can always be converted to logarithms where the low is 2, so even when multi-value technology is used, information is still described in bits.

[0006] In contrast, the human brain is not made up of memory elements. If there were something that corresponds to a memory element, it would be the cell body that makes up part of the nerve cell, but this cell body does not store information such as 0 or 1.

[0007] As shown simply in Figure 1, a nerve cell (neuron) generally consists of three parts: a cell body, multiple (e.g., dozens) dendrites, and an axon. The cell body can receive external input from these multiple dendrites. The axon generally extends longer than the dendrites, and its tip further branches into tens to hundreds of branches. The tip of these branched axons is called the axon terminal.

[0008] As shown simply in Figure 2, the axon terminal approaches one of the dendrites of another cell body and forms a junction called a synapsis.

[0009] There are now two cell bodies, cell A and cell B. Cell body A receives multiple external inputs x(n) through multiple dendrites (n), where n is an integer between 1 and N. Cell body A assigns a weight W(n) to each input x(n). The signal summed according to these weights is called SUM. SUM is transferred to one of the axon terminals via the axon. When SUM exceeds a certain threshold (threshold of exitation), the neuron generates an action potential, driving synapsis and transmitting neurotransmitters from cell body A to cell body B.

[0010] This threshold changes as signals are transmitted repeatedly. In other words, by repeatedly learning from experience, synaptic connections become stronger, break, or are replaced. The strengthening of synaptic connections can be explained by a lowering of the threshold. The disconnection of synapses can be explained by a rising of the threshold. The replacement of synapses can be explained by a change in the distribution of synaptic thresholds.

[0011] This is modeled as shown in Figure 3. When neurotransmitters are transmitted, the output y is set to 1 (y=1), and when not, it is set to y=0. This model is called a perceptron, and is widely used in deep learning and machine learning.

[0012] There are two main ways to implement a perceptron on a computer.

[0013] In the traditional method, the input x(n), weight w(n), SUM, threshold, and output y are all represented as bits, i.e., a computer program.

[0014] The problem with this method is that it places a heavy load on computers. There is a greater need than ever before to improve calculation speeds and reduce power consumption. Deep learning and machine learning require the instantaneous processing of huge amounts of data, and if calculations that place a heavy load were to flood the world, the power consumption of data centers would increase explosively, making it difficult to operate them practically. Furthermore, there are growing concerns that this could accelerate global warming (see Non-Patent Document 2).

[0015] The main cause of the limit on computing speed is excessive data communication between the processor and main memory. Although processors can still be made faster, the communication speed of the data bus between the processor and main memory has reached a ceiling. This is called the von Neumann bottleneck (or memory bus problem).

[0016] The main reason for this increase in power consumption is that the main memory devices currently in use are volatile memory devices called dynamic random access memory (DRAM), which means that the power consumed by refreshing recorded data is becoming non-negligible.

[0017] A recent trend is to replicate the perceptron directly on a semiconductor chip in order to avoid the von Neumann bottleneck and simultaneously reduce power consumption. However, the neural networks of the human brain are generally designed to generate synapses between two unspecified pairs of neurons. While current semiconductor technology makes it possible to place perceptrons at precisely specified addresses on a two-dimensional plane or in three-dimensional space, it is not easy to replicate synapses between arbitrary pairs of neurons or to freely reassign them according to learning.

[0018] Furthermore, as mentioned above, while information is recorded in bits in existing memory architectures, the human brain represents information in the form of connections between neurons (neural networks), i.e., synapses. In other words, reproducing deep learning or machine learning on a program written in bits of information means that an entire program has already been written to model one unit of a neural network (perceptron). This results in a significant loss of information processing.

[0019] For example, suppose a perceptron program can be written in about 1,000 lines. If each line contains 80 bytes (1 byte is 8 bits), then 80 kilobytes of information is required to recreate a perceptron as a computer program. Even if the program could be compiled and compressed to one-tenth the size, it would still only be 8 kilobytes. If this could be recreated in 100 bits on a semiconductor chip, then the computer program would waste 640 times the amount of information per perceptron.

[0020] The total number of neurons in the entire human brain (cerebrum and cerebellum) is said to be approximately 86 billion. Let's assume that a human uses 1% of these neurons per hour. If we further assume that the number of neurons and the number of perceptrons are roughly equal, the amount of information that would be wasted in order to achieve artificial intelligence with human-level capabilities can be calculated as (8 kilobytes - 100 bits) times 860 million. This works out to roughly 7 terabytes per hour. This means that the computer would be forced to process a huge amount of information unnecessarily.

[0021] Deep learning and machine learning technologies are not yet at a level comparable to the human brain. Therefore, as AI advances, the amount of information computers are forced to process unnecessarily will likely continue to increase. If such AI becomes widespread in the future, how large will the global population be? A population of 1 million would mean the world would waste 7 exabytes of information per hour. Even if the shift from fossil fuels to renewable energy were to dramatically reduce the share of fossil fuels in the electricity consumed by computers worldwide for AI to 30%, processing 2.1 exabytes per hour would still require unnecessary fossil fuel burning. In other words, unless the power consumption associated with information processing can be dramatically reduced, the spread of AI could compete with efforts to curb climate change. If climate change prevention is prioritized, the number of AIs with human-level or higher levels of sophistication will be limited, and a few super-large corporations and superpowers will monopolize this enormous computing power and use up all of our carbon dioxide emission quotas. This is certainly not a bright future.

[0022] Next, we compare the amount of information in the network with the amount of information in bits.

[0023] The study of networks is called graph theory in mathematics. A network is generally a collection of multiple points connected by multiple lines. In contrast, bit-based information processing involves processing information only at points, without any lines.

[0024] The points mentioned above are called vertices or nodes. The lines connecting the nodes or vertices are called edges or links. Nodes and links are terms preferred by physics, but they refer to the same thing as vertices and edges, respectively.

[0025] To begin with, networks are complex, and in order to accurately estimate the amount of information in a network, significant limitations must be imposed. Figure 4 shows an example of this.

[0026] When connecting any two points (1 and 2), if the direction from 1 to 2 and the direction from 2 to 1 are considered to be different links, it is called a directed network. If not, it is called an undirected network. In a directed network, links are represented by arrows, as shown in Figure 4. The start and end points are represented by circles. See the case where r=2 in Figure 4. There are two possible combinations with two circles and one arrow. Here, r is the number of nodes to be linked.

[0027] When r = 3, two arrows are short-circuited, connecting the start point and the end point. The number of cases in this case is 6. When r = 4, three arrows are short-circuited, connecting the start point and the end point. The number of cases in this case is 8. If the total number of nodes is N, the number of cases where the number of linked nodes is r is expressed as the product of r and the permutation P(N,r) of N and r. Adding this product from 3 to N and then adding P(N,2) gives the number of cases for the network under this constraint. This is obviously greater than the factorial of N (N!).

[0028] Although this does not cover all network possibilities, it is possible to show that even such a highly constrained network has a larger information content than a bit.

[0029] Consider a case where N nodes are distributed across a memory cell array. The amount of information per bit is simply N bits. In contrast, the amount of information in the example network shown in Figure 4 is greater than log(2, N!), where log(2, x) is the base 2 logarithm of x.

[0030] Using Stirling's rule, when N is large enough (effectively at least greater than 20), log(2,N!) is (Nlog(e,N)-N) / log(e,2), where log(e,x) is the logarithm of x to the base e. Dividing this value by N gives (log(e,N)-1) / log(e,2), which is greater than 1 when N is large enough.

[0031] When converted to 128Gbit DRAM, the number of nodes (N) is roughly 10 to the 11th power. Since log(2, e) is approximately 1.9, looking at Figure 5, it is obvious that the amount of information in the network in Figure 4 will be much larger than the amount of information in bits.

[0032] Next, in a network, information can be recorded that has different paths even if the starting point and the end point are the same.

[0033] Figure 6 shows several examples of paths from a starting point (1) to an end point (2), including two, three, four, and five links from the left.

[0034] When there are two links, there is an intermediate node between the start point (1) and the end point (2). Depending on the address of this intermediate node, the signal flowing into the end point (2) may differ.

[0035] When there are three links, there are two intermediate nodes between the starting point (1) and the end point (2). Depending on the order of the addresses of these two intermediate nodes, the signal flowing into the end point (2) may be different. Furthermore, we must also take into account cases where the addresses of the intermediate nodes change.

[0036] When there are four links, there are three intermediate nodes between the starting point (1) and the end point (2). Depending on the order of the addresses of these three intermediate nodes, the signal flowing into the end point (2) may differ. Furthermore, we must also take into account cases where the addresses of the intermediate nodes change.

[0037] When there are five links, there are four intermediate nodes between the starting point (1) and the end point (2). Depending on the order of the addresses of these four intermediate nodes, the signal flowing into the end point (2) may differ. Furthermore, we must also take into account cases where the addresses of the intermediate nodes change.

[0038] Thus, it can be seen that the amount of information that a network can store is much greater than the amount of information stored by bits with the same number of nodes.

[0039] As far as computers are concerned, the most common type today is a Turing machine, which is actually made up of at least two silicon chips connected by a memory bus.

[0040] In other words, the object of this application is to integrate a neural network onto a silicon chip without relying on bit operations. DISCLOSURE OF THE INVENTION [Problem to be solved by the invention]

[0041] The present invention has been made in view of the above circumstances, and provides a method for integrating a network-based information processing system into a silicon chip. [Means for solving the problem]

[0042] In order to solve the above problems, the present invention employs the following means.

[0043] The solution proposed by the present invention is a plurality of islands periodically arranged on a semiconductor surface in a first axis direction and a second axis direction; first and second links, each of which is disposed between two islands adjacent to each other in the first and second directions among the plurality of islands; a first word line in a third axis direction; a second word line in a fourth axial direction; and each of the plurality of islands includes a diffusion layer formed on the semiconductor surface; the first link is a first selection gate that bridges two islands that are adjacent to each other in the first direction among the plurality of islands, the second link is a second selection gate that bridges two islands that are adjacent to each other in the second direction among the plurality of islands, the first and second select gates each having a select gate contact; the select gate contacts are selected by the first and second word lines; One of the plurality of islands the first select gate is disposed in the first axial direction; the second select gate is disposed in the second axial direction; the first word line is in a first wiring layer; the second word line is in a second wiring layer; It is characterized by the fact that

[0044] Further, a contact transistor is provided, The contact transistor has a contact gate and two terminals; the contact gate connects to the first word line; one of the two terminals is connected to the second word line; the other of the two terminals is connected to the select gate contact; It is characterized by the fact that

[0045] or, further comprising two contact transistors in series with each other; the two-contact transistor has two contact gates and two terminals; one of the two contact gates connects to the first word line; the other of the two contact gates is connected to the second word line; one of the two terminals connects to the select gate contact; It is characterized by the fact that

[0046] Furthermore, further comprising a bit line and a third select gate; the third select gate has a select gate contact and two terminals; one of the two terminals of the third select gate is connected to the bit line and serves as a bit line contact; the other of the two terminals of the third select gate is connected to one of the islands; a select gate contact of the third select gate is selected by the first and second word lines;

[0047] Furthermore, it is equipped with an operational amplifier, the operational amplifier is connected to the bit line and compares the potential of the bit line with a predetermined threshold potential; If the potential of the bit line is higher than the threshold potential, output data 1; If the potential of the bit line is lower than the threshold potential, output data 0; further comprising first and second bit line select gates and a source line; the first bit line select gate is disposed between the bit line contact and the operational amplifier; the second bit line select gate is disposed between the bit line contact and the source line;

[0048] Further, a capacitor is provided, the capacitor is disposed between the first and second bit line select gates; connected to the bit line, It is characterized by: [Effects of the Invention]

[0049] According to the present invention, it is possible to reproduce the information processing method of the human brain (simply a neural network) on a silicon chip (IC chip) without converting it into bit data. The best mode for carrying out the invention will now be described in detail. BEST MODE FOR CARRYING OUT THE INVENTION

[0050] As mentioned above, this invention proposes a method for reproducing the information processing method of the human brain on a semiconductor chip (silicon chip) without converting it into bit information (without relying on a computer program). This will be explained in detail below with reference to the drawings.

[0051] FIG. 7 is a diagram illustrating an example of a circuit diagram for integrating the neural network of the present invention on an IC chip.

[0052] The white dots represent islands in the circuit, which correspond to dendrites and synapses. The black dots represent bit line contacts that correspond to axon terminals. The open squares represent select gates (SG), and the black dots within them represent the gate contacts of the select gates (GC).

[0053] Axon terminals and dendrites join at bit line contacts to form synapses, and signals are input to the soma body through these synapses. In this diagram, as an example, three axon terminals (bit line contacts) are connected in parallel to the same k-th bit line BL(k). In other words, this bit line corresponds to the soma body. There is not necessarily only one soma body. Generally, k is a natural number.

[0054] The signal from the dendrite is input as a displacement voltage of the bit line (cell body), and a capacitor is connected to the bit line BL(k) to maintain (stabilize) that voltage displacement for a certain period of time. In an integrated circuit, such a capacitor can be constructed using parasitic capacitance, etc. Alternatively, a separate capacitor can be integrated.

[0055] The bit line contact is further sandwiched between a source side bit line select gate BLSGS(k) and a drain side bit line select gate BLSGD(k). The capacitor (capacitance) is also preferably sandwiched between these two bit line select gates. A source line is located on the source side, and the source side bit line select gate is preferably installed between this source line and the bit line contact.

[0056] Ahead of the drain-side bit line select gate, there can be provided a circuit such as an operational amplifier (shown as a diamond shape in the figure) that compares the threshold (threshold potential, Threshold of excitation) with the potential of the bit line, and a sense amplifier that adjusts the signal from this operational amplifier circuit and outputs data 1 or 0 to an external circuit. In other words, if the bit line potential is higher than the threshold (threshold potential), the sense amplifier (S / A) amplifies the signal from the operational amplifier and outputs data 1. If not, data 0 is output from the S / A. If the performance of the operational amplifier circuit is sufficient and the output is clearly divided into data 1 and data 0, the sense amplifier can be omitted. In this way, it is desirable to install the drain-side bit line select gate between the operational amplifier circuit and the bit line contact. Also,

[0057] The select gates, which are not directly connected to the bit line BL(k), are arranged between the islands and connect or disconnect the link between the islands. That is, when the select gate is on, the link is connected, and when it is off, the link is disconnected. In general, it is desirable that the two islands bridged by the link be adjacent to each other.

[0058] In other words, the islands are the nodes of the network, and the select gates in the on state are the links of the network. The islands can be connected to a buried wiring rail (BWR) buried in the semiconductor substrate.

[0059] FIG. 8 is a diagram illustrating an example of a select gate of the present invention.

[0060] (A) on the left shows an equivalent circuit diagram of the select gate used in Figure 7. The white dots on both sides represent islands (nodes) that are dendrites or axon terminals, and the black dot in the center represents a select gate contact (GC). The select gate consists of one select gate contact GC and two terminals that can pass current. When these terminals are connected to an island (node), the terminal becomes an island in terms of the circuit. When these terminals are connected to a bit line, the terminal becomes a bit line contact in terms of the circuit. (B) shows the case where this select gate is a nonvolatile memory cell with a charge storage layer. In other words, the threshold voltage Vt of this nonvolatile memory cell records the on / off state of the link in Figure 7. If Vt is high, the link is off, and if Vt is low, the link is on. A link on means that the link is connected, and the two white dots (nodes) on the left and right are linked (connected). A link off means that the line is disconnected, and the two white dots (nodes) on the left and right are not linked (disconnected).

[0061] (C) shows a memory cell in which the select gate has a variable resistance. Any type of variable resistance can be used, including magnetic variable resistance, phase-change variable resistance, ferroelectric variable resistance, and metal-insulator variable resistance. The threshold resistance Rt of this variable resistance memory cell records the on / off state of the link in Figure 7. A high Rt indicates that the link is off, and a low Rt indicates that the link is on. A link on indicates that the link is connected, and the two white dots (nodes) on the left and right are linked (connected). A link off indicates that the link is disconnected, and the two white dots (nodes) on the left and right are not linked (disconnected).

[0062] FIG. 9 is a diagram illustrating an example of how the network of the present invention is integrated.

[0063] The islands (nodes) in Figures 7 and 8 are regions on the semiconductor surface that include a diffusion layer formed on the semiconductor surface, or the diffusion layer itself. There is a channel between two islands (diffusion layers) on the semiconductor surface; if the diffusion layer is N+ type, the channel will be P-type; if the diffusion layer is P+ type, the channel will be N-type. The channel surface is covered with a gate oxide film, on which a gate (G) is formed to bridge the two diffusion layers. The gate (or gate electrode) is preferably made of high-concentration polysilicon, metal, etc.

[0064] Figure 9 shows an efficient layout for integrating nodes (diffusion layers) and gates. The left side shows an equivalent circuit, representing a unit extracted from the layout in Figure 7. The right side shows the integration method used to achieve this. A checkerboard-like layout unit is constructed from four diffusion layers (nodes) and four gates (links) within a well formed on the semiconductor surface. The checkerboard pattern here refers to the periodic arrangement of structures (components) along two non-parallel axes in a plane. If the diffusion layers are N+ type, the well is P-type; if the diffusion layers are P+ type, the well is N-type. This layout does not require a buried power rail (BPR). One island has a gate along the first axis (e.g., the X direction) and another gate along the second axis (e.g., the Y direction). Alternatively, adjacent islands along the first axis are bridged by a gate, and adjacent islands along the second axis are bridged by another gate.

[0065] FIG. 10 is a diagram illustrating an example of how the network of the present invention is integrated.

[0066] Figure 10 shows the units of Figure 9 arranged vertically and horizontally. Many of the above units are integrated in a common well.

[0067] To actually operate the equivalent circuit in Figure 7, each select gate (link) must be able to be freely switched on and off.

[0068] In this diagram, select gates (G) are placed between nodes (diffusion layers) laid out in a checkerboard pattern within the well. This means that the select gate contacts (GC) of the select gates (G) are also laid out in a checkerboard pattern on the semiconductor surface, and each must be freely selectable. This type of gate wiring does not exist in ordinary IC chip products.

[0069] FIG. 11 is a diagram illustrating an example of a wiring layout according to the present invention.

[0070] Islands (nodes) are represented by white dots, and the links connecting the islands (nodes) are represented by select gates in Figure 8(A). The select gates have select gate contacts (GC), and a feature of this application is that each select gate contact must be arbitrarily accessible. "Arbitrary access" means that any select gate can be selected and freely switched on / off.

[0071] The select gate is located at the intersection of the X-axis word line WLX, represented by a dashed line, and the Y-axis word line WLY, also represented by a dashed line. The angle between WLX and WLY can be any angle between 0 and 180 degrees. Considering the degree of integration, a 90-degree angle is generally desirable. In any case, at least two axial word lines that are not parallel to each other are required to select the select gate contact.

[0072] Since the links (solid lines) and the word lines (dashed lines) overlap, a diagram in which the links (solid lines) are omitted from FIG. 11 is shown in FIG.

[0073] Word lines are numbered in both the X-axis and Y-axis directions. Links (select gates) are arranged at every other WLX along the jth Y-axis word line WLY(j). Similarly, links (select gates) are arranged at every other WLY along the i-th X-axis word line WLX(i).

[0074] That is, the select gates are placed at the points where WLX(i) intersects with WLY(j-3), WLY(j-1), WLY(j+1), etc. The select gates are placed at the points where WLY(j) intersects with WLX(i-3), WLX(i-1), WLX(i+1), etc. These intersections where the select gates are placed are called selection intersections.

[0075] Metal wiring such as word lines and bit lines is formed by a wiring process after forming the node (diffusion layer) and the select gate contact GC of the link (select gate), etc. Therefore, the wiring layer is formed on the select gate contact GC.

[0076] Generally, multiple wiring layers are stacked, and the X-axis word line and the Y-axis word line are actually formed in separate wiring layers. For example, if the X-axis word line WLX is formed in the kth metal layer (Mk layer), the Y-axis word line WLY is formed in the k'th metal layer (Mk' layer). Generally, k and k' are two different integers.

[0077] FIG. 13 is a diagram showing an example of a method for connecting WLX(i) in the Mk layer and WLY(j+1) in the Mk′ layer at a selection intersection.

[0078] The wiring connection transistor (connection transistor) has a contact gate and two terminals that can conduct current. WLX(i) of the Mk layer is connected to the contact gate, and WLY(j+1) of the Mk' layer is connected to one of the diffusion layers of the connection transistor. A select gate contact GC of the select gate is connected to the other diffusion layer of the connection transistor. Although this is self-evident and not specifically shown, WLY(j+1) may be connected to the gate (contact gate) of one connection transistor, and WLX(i) may be connected to one of the diffusion layers of the connection transistor.

[0079] The contact transistors are arranged at the selection intersections. That is, they are arranged at the points where WLX(i) intersects with WLY(j-3), WLY(j-1), WLY(j+1), etc., and where WLY(j) intersects with WLX(i-3), WLX(i-1), WLX(i+1), etc. In other words, when one WLX is selected, every other WLY is selected so that it intersects with that WLX. When one WLY is selected, every other WLX is selected so that it intersects with that WLY. The reason for this alternating selection is obvious from Figure 7. That is, there is both a selection gate that bridges (links) two islands adjacent in a first direction (for example, the X-axis direction) and a selection gate that bridges (links) two islands adjacent in a second direction (for example, the Y-axis direction).

[0080] 14A and 14B are diagrams illustrating an example of a connection transistor, in which (A) in FIG. 14 corresponds to the example of the connection transistor in FIG. 13, and (B) in FIG. 14 is another example.

[0081] (A) shows an example where a selection cross point is formed with one contact transistor. In other words, one contact gate and two terminals (for example, diffusion layers) form the connection at the selection cross point. (B) shows an example where two contact transistors connected in series form one selection cross point. In other words, two of the four terminals (for example, diffusion layers) are shared or shorted with each other, so two contact gates and two terminals form the connection at the selection cross point.

[0082] For simplicity, k = 0 and k' = 1 are used below. In (A), WLX(i) in the M0 layer is connected to the contact gate of the connection transistor, and WLY(j+1) in the M1 layer is connected to one terminal of the connection transistor. The remaining terminal is connected to the select gate contact GC of the select gate. When a high voltage is applied to WLX(i) and the connection transistor is turned on, the voltage of WLY(j+1) is applied to the select gate contact GC. In (B), WLX(i) in the M0 layer is connected to one of the two contact gates, and WLY(j+1) in the M1 layer is connected to the other contact gate. One of the two diffusion layers is connected to the select gate contact GC, and the other is connected to a power supply or other power source separately connected to the M2 layer. When a high voltage is applied to both WLX(i) and WLY(j+1) and the two connection transistors are simultaneously turned on, the voltage of the power supply separately connected to the M2 layer is applied to the select gate contact GC.

[0083] Figure 15 shows two examples corresponding to Figure 14(A). (A1) shows the case where the select gate is (B) in Figure 8 (non-volatile memory cell). (A2) shows the case where the select gate is (C) in Figure 8 (variable resistance memory cell).

[0084] Figure 16 shows two examples corresponding to Figure 14(B). (B1) shows the case where the select gate is (B) in Figure 8 (non-volatile memory cell). (B2) shows the case where the select gate is (C) in Figure 8 (variable resistance memory cell).

[0085] The metal wiring in Figure 12 is arranged in the same axial direction as the underlying link. However, since the metal wiring is on a different layer from the underlying link, it does not matter if the axial direction is in a different direction from the underlying link.

[0086] Figure 17 shows an example in which word line WL3 is oriented in a third axis direction, different from both the X and Y axes in the XY plane, and word line WL4 is oriented in a fourth axis direction, different from the X, Y, and third axes in the XY plane. In other words, both WL3 and WL4 are oriented in a different direction from the underlying links. Considering integration density, it is desirable to arrange WL3 and WL4 so that they are perpendicular to each other. In this figure, both WL3 and WL4 are represented by dashed lines. It is particularly desirable that the X and Y axes are perpendicular to each other, and that the angle between the X and WL3 is approximately 45 degrees. In practice, it is not easy to manufacture a device in which the angle between the X and WL3 is exactly 45 degrees. Therefore, it is desirable to set the angle between 30 and 60 degrees.

[0087] As in the example above, WL3 and WL4 are formed in the wiring layer. For example, WL3 is formed in the Mk layer, and WL4 is formed in the Mk' layer. A select gate is located at the address corresponding to the intersection of WL3 and WL4 (selection intersection).

[0088] WL3(i) of the Mk layer is connected to the contact gate of a transistor (contact transistor) for wiring connection, and WL4(j) of the Mk' layer is connected to one terminal of the contact transistor. The select gate contact GC of the select gate is connected to the other terminal of the contact transistor. Although this is self-evident and not specifically shown, it is also possible to connect WLY(j) to the gate (contact gate) of the contact transistor, and connect WLX(i) to one terminal of the contact transistor.

[0089] The contact transistors are placed at the selection intersections. That is, they are placed at the points where WL3(i) intersects with WL4(j-2), WL4(j-1), WL4(j), WL4(j+1), etc., and where WL4(j) intersects with WL3(i-1), WL3(i), WL3(i+1), etc. Unlike the case of Figure 12, the selection intersections are not placed every other intersection. This is shown in Figure 21.

[0090] 18A and 18B are diagrams illustrating an example of a connection transistor, in which (A) in FIG. 18 corresponds to the example of the connection transistor in FIG. 21, and (B) in FIG. 18 is another example.

[0091] (A) shows an example where a selection crosspoint is formed with one contact transistor. That is, one contact gate and two diffusion layers form the connection at the selection crosspoint. (B) shows an example where two contact transistors connected in series form one selection crosspoint. That is, two of the four diffusion layers are shared or shorted with each other, so two contact gates and two diffusion layers form the connection at the selection crosspoint.

[0092] For simplicity, k = 0 and k' = 1 are used below. In (A), WL3(i) in the M0 layer is connected to the gate (contact gate) of the connection transistor, and WL4(j) in the M1 layer is connected to one terminal of the connection transistor. The remaining terminal is connected to the select gate contact GC of the select gate. When a high voltage is applied to WL3(i) and the connection transistor is turned on, the voltage of WL4(j) is applied to the select gate contact GC. In (B), WL3(i) in the M0 layer is connected to one of the two contact gates, and WL4(j) in the M1 layer is connected to the other contact gate. One of the two diffusion layers is connected to the select gate contact GC, and the other is connected to a power supply or other power source separately connected to the M2 layer. When a high voltage is applied to both WL3(i) and WL4(j) and the two connection transistors are simultaneously turned on, the voltage of the power supply separately connected to the M2 layer is applied to the select gate contact GC.

[0093] Figure 19 shows two examples corresponding to Figure 18(A). (A1) shows the case where the select gate is (B) in Figure 8 (non-volatile memory cell). (A2) shows the case where the select gate is (C) in Figure 8 (variable resistance memory cell).

[0094] Figure 20 shows two examples corresponding to Figure 18(B). (B1) shows the case where the select gate is (B) in Figure 8 (non-volatile memory cell). (B2) shows the case where the select gate is (C) in Figure 8 (variable resistance memory cell).

[0095] [Non-Patent Document 1] Goodon E. Moore, “Cramming more components onto integrated circuits”, Electronics, volume 38, Number 8, April 19, 1965.

[0096] [Non-patent document 2] Masanet, E.; Shhehabi, A.; Lei, N.; Smith, S.; Koomey, J. Recalibrating global data center energy-use estimates. Science 2020, vol. 3667, 984―986.

[0097] The features of the present invention have been described above. Finally, the technical scope of the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit of the present invention.

[0098] [Industrial Applicability]

[0099] Silicon technology will make it possible to provide a method for realizing the information processing mechanisms of the human brain on semiconductor chips. [Brief explanation of the drawings]

[0100] [Figure 1] A diagram illustrating an example of a nerve cell. [Figure 2] 1 is a diagram illustrating an example of synapsis. [Figure 3] An example diagram illustrating the concept of a perceptron. [Figure 4] A diagram illustrating an example of a method for counting the number of links between two points. [Figure 5] A plot of the ratio of the network information volume to the bit information volume (number of bits) against the number of nodes (N). [Figure 6] A diagram showing that even if the start and end points are the same, the input to the end point may be different if the path (route) is different. [Figure 7] 1 is a diagram illustrating an example of a circuit diagram for integrating the neural network of the present invention on an IC chip. [Figure 8] 1 is a diagram illustrating an example of a select gate according to the present invention. [Figure 9]1 is a diagram illustrating an example of how the network of the present application is integrated. [Figure 10] 1 is a diagram illustrating an example of how the network of the present application is integrated. [Figure 11] 1 is a diagram illustrating an example of a wiring layout according to the present invention. [Figure 12] 1 is a diagram illustrating an example of a wiring layout according to the present invention. [Figure 13] 1 is a diagram illustrating an example of a layout of a contact transistor of the present application. [Figure 14] 1 is a diagram illustrating an example of a contact transistor of the present application. [Figure 15] 1 is a diagram illustrating an example of a contact transistor of the present application. [Figure 16] 1 is a diagram illustrating an example of a contact transistor of the present application. [Figure 17] 1 is a diagram illustrating an example of a wiring layout according to the present invention. [Figure 18] 1 is a diagram for explaining an example of wiring to a select gate of the present application. [Figure 19] 1 is a diagram for explaining an example of wiring to a select gate of the present application. [Figure 20] 1 is a diagram for explaining an example of wiring to a select gate of the present application. [Figure 21] 1 is a diagram illustrating an example of a wiring layout according to the present invention.

Claims

1. a plurality of islands periodically arranged on a semiconductor surface in a first axis direction and a second axis direction; first and second links, each of which is disposed between two islands adjacent to each other in the first and second directions among the plurality of islands; a first word line in a third axis direction; a second word line in a fourth axial direction; and each of the plurality of islands includes a diffusion layer formed on the semiconductor surface; the first link is a first selection gate that bridges two islands that are adjacent to each other in the first direction among the plurality of islands, the second link is a second selection gate that bridges two islands that are adjacent to each other in the second direction among the plurality of islands, the first and second select gates each having a select gate contact; the select gate contacts are selected by the first and second word lines; A semiconductor device characterized by:

2. One of the plurality of islands the first select gate is disposed in the first axial direction; the second select gate is disposed in the second axial direction; 2. The semiconductor device according to claim 1.

3. Further, a contact transistor is provided, The contact transistor has a contact gate and two terminals; the contact gate connects to the first word line; one of the two terminals is connected to the second word line; the other of the two terminals is connected to the select gate contact; 2. The semiconductor device according to claim 1.

4. further comprising two contact transistors in series with each other; the two-contact transistor has two contact gates and two terminals; one of the two contact gates connects to the first word line; the other of the two contact gates is connected to the second word line; one of the two terminals connects to the select gate contact; 2. The semiconductor device according to claim 1.

5. the first word line is in a first wiring layer; the second word line is in a second wiring layer; 2. The semiconductor device according to claim 1.

6. further comprising a bit line and a third select gate; the third select gate has a select gate contact and two terminals; one of the two terminals of the third select gate is connected to the bit line and serves as a bit line contact; the other of the two terminals of the third select gate is connected to one of the islands; a select gate contact of the third select gate is selected by the first and second word lines; 2. The semiconductor device according to claim 1.

7. Furthermore, it is equipped with an operational amplifier, the operational amplifier is connected to the bit line and compares the potential of the bit line with a predetermined threshold potential; If the potential of the bit line is higher than the threshold potential, output data 1; If the potential of the bit line is lower than the threshold potential, data 0 is output.

7. The semiconductor device according to claim 6.

8. further comprising first and second bit line select gates and a source line; the first bit line select gate is disposed between the bit line contact and the operational amplifier; the second bit line select gate is disposed between the bit line contact and the source line; 8. The semiconductor device according to claim 7.

9. Further, a capacitor is provided, the capacitor is disposed between the first and second bit line select gates; connected to the bit line, 9. The semiconductor device according to claim 8.

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