High-speed writing method and system for solid-state storage device

Abstract

The invention relates to the technical field of data processing, in particular to a solid-state storage device high-speed writing method and system. The writing method comprises the following steps: applying a specific pulse voltage to two ends of a storage unit of the solid-state storage device, so that electrons can perform quantum tunneling through an insulating layer, and a quantum tunneling condition is generated for writing data with low power consumption; the method comprises the following steps of: preprocessing the storage units, namely initializing, detecting a state and repairing an insulating layer, so as to ensure that each storage unit is in a state suitable for writing; according to the high-speed write-in method and system of the solid-state storage device, the problem that low power consumption and high stability of the solid-state storage device in the high-speed write-in process are difficult to consider at the same time in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a high-speed writing method and system for a solid-state storage device. Background Art

[0002] With the continuous improvement of storage density and the increasing complexity of application requirements, solid-state storage devices face a series of technical challenges in the high-speed writing process. The writing method of traditional solid-state storage devices mainly relies on the charge trap storage mechanism, and its writing speed and power consumption are limited by material properties and environmental conditions. Especially in high-frequency and large-data volume writing operations, charge accumulation and insulation layer damage in storage cells can lead to increased write latency, data loss and shortened storage life. In addition, although multi-core parallel writing technology can improve writing speed, it lacks effective writing parameter optimization and real-time monitoring mechanism, and it is difficult to maintain stability and reliability in complex environments.

[0003] The present invention aims to solve the main technical problems existing in the high-speed writing process of existing solid-state storage devices: that is, how to achieve high-speed writing with low power consumption and high stability while ensuring the integrity and reliability of data. Summary of the invention

[0004] The present invention provides a solid-state storage device high-speed writing method and system to solve the technical problems of high power consumption and instability during high-speed writing of the solid-state storage device.

[0005] The technical solution of the present invention to solve the above technical problems is as follows: In one aspect, a high-speed writing method for a solid-state storage device is provided, the writing method comprising the following steps: Applying a specific pulse voltage across the storage unit of the solid-state storage device enables electrons to quantum tunnel through the insulating layer, generating quantum tunneling conditions for writing data with low power consumption; Preprocessing the storage unit, the preprocessing steps include initialization, state detection and insulation layer repair, to ensure that each storage unit is in a state suitable for writing; Determine optimal write parameters through an adaptive quantum tunneling algorithm, which dynamically adjusts voltage and current based on the current state of the solid-state storage device and environmental conditions to optimize write speed; Use parallel quantum tunneling to write to multiple storage cells simultaneously, with each storage cell independently controlled to reduce write latency; Real-time monitoring and feedback of the writing process. Built-in sensors are used to detect the motion state of electrons and the physical properties of storage cells during the writing process, and the writing parameters are adjusted according to the feedback results. The data written to the solid-state storage device is verified using a verification algorithm to ensure the integrity of the data.

[0006] On the other hand, a high-speed writing system for a solid-state storage device is provided, the writing system comprising: A voltage generation module, implemented by a high-precision voltage controller, is used to generate pulse voltage under quantum tunneling conditions; A pre-processing module, including charge balancing, state detection and insulation layer repair, is used to pre-process the storage unit; An adaptive quantum tunneling algorithm module that dynamically adjusts write parameters based on the current state of the storage device and environmental conditions; A parallel writing module, which writes to multiple storage cells simultaneously through a multi-core control circuit to achieve parallel quantum tunneling; A real-time monitoring module uses sensors to detect the electron motion state and physical characteristics of the storage unit during the writing process to provide real-time feedback; The data verification module uses self-verification based on quantum tunneling to ensure data integrity and accuracy; A cryogenic cooling module that uses active and passive cooling techniques to keep the temperature of the storage unit within an optimal range to improve the stability of quantum tunneling; A wear leveling module performs wear leveling on storage units to extend the life of storage devices; The multi-layer data verification mechanism module is used to improve the reliability of data writing through multi-layer verification at the physical layer, logical layer and application layer; Communication interface module, supporting multiple data transmission protocols, used to achieve communication with external devices; The power management module provides power supply and energy optimization for the writing system.

[0007] The beneficial effects of the present invention are: The high-speed writing method and system of the solid-state storage device of the present invention solves the problem in the prior art that it is difficult to balance low power consumption and high stability during high-speed writing of solid-state storage devices. Specifically, parallel quantum tunneling technology is adopted, and by applying a specific high-frequency, low-amplitude pulse voltage at both ends of the storage unit, electrons can perform quantum tunneling through the insulating layer efficiently and with low power consumption, thereby achieving high-speed data writing. The adaptive quantum tunneling algorithm dynamically adjusts the writing parameters according to the current state and environmental conditions of the storage device to ensure that each storage unit is in the optimal writing state, thereby improving the writing speed and stability. Furthermore, through real-time monitoring and feedback mechanisms, the system can detect the motion state of electrons and the physical characteristics of the storage unit during the writing process, and adjust the writing parameters in real time according to the feedback results, effectively reducing the writing delay. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 The figure is a flow chart of a high-speed writing method for a solid-state storage device according to an embodiment of the present invention.

[0009] Figure 2 Schematic diagram of quantum tunneling principle in one embodiment of the present invention.

[0010] Figure 3 This is a pulse voltage waveform diagram under quantum tunneling conditions in one embodiment of the present invention.

[0011] Figure 4 Schematic diagram of parallel quantum tunneling writing order optimization in one embodiment of the present invention.

[0012] Figure 5 FIG. 1 is a diagram showing changes in temperature and cooling power during a writing process in one embodiment of the present invention.

[0013] Figure 6 This is a comparison diagram before and after wear leveling processing in one embodiment of the present invention.

[0014] Figure 7 Schematic diagram of a multi-layer data verification mechanism in one embodiment of the present invention. DETAILED DESCRIPTION

[0015] The present invention provides the following preferred embodiments: Embodiment 1 In order to solve the problems of slow writing speed and high power consumption of existing solid-state storage devices, this embodiment proposes a high-speed writing method for solid-state storage devices, and its flow chart is as follows: Figure 1 The writing method achieves low power consumption and high-speed data writing by precisely controlling the pulse voltage parameters so that electrons can effectively perform quantum tunneling through the insulating layer, such as Figure 2 shown.

[0016] refer to Figure 1 , the steps of the high-speed writing method of solid-state storage device include: S100, applying a specific pulse voltage across the storage unit of the solid-state storage device to enable electrons to quantum tunnel through the insulating layer, thereby generating quantum tunneling conditions for writing data with low power consumption.

[0017] S200, preprocessing the storage unit, the preprocessing steps including initialization, state detection and insulation layer repair, to ensure that each storage unit is in a state suitable for writing.

[0018] S300, determining optimal write parameters through an adaptive quantum tunneling algorithm, the adaptive quantum tunneling algorithm dynamically adjusts voltage and current according to the current state and environmental conditions of the solid-state storage device to optimize the write speed.

[0019] S400 uses parallel quantum tunneling to write to multiple storage cells simultaneously, and each storage cell is independently controlled to reduce write latency.

[0020] S500, real-time monitoring and feedback of the writing process are performed, the movement state of electrons and the physical characteristics of the storage unit during the writing process are detected by built-in sensors, and the writing parameters are adjusted according to the feedback results.

[0021] S600: Use a verification algorithm to verify the data written into the solid-state storage device to ensure the integrity of the data.

[0022] Specifically, a specific pulse voltage is applied across the storage unit of the solid-state storage device. The frequency range of the pulse voltage is set to 100 MHz to 200 MHz, and the amplitude range is set to 0.5 V to 1.5 V. The selection of these parameters is based on the physical properties of the quantum tunneling effect and the material properties of the storage unit. It should be understood that the frequency and amplitude of the pulse voltage affect the quantum tunneling effect. Too high or too low frequency and amplitude will affect the tunneling efficiency of electrons, thereby affecting the writing speed and power consumption. By precisely controlling these parameters, data writing can be ensured under optimal conditions.

[0023] Further, the storage cell is preprocessed. The preprocessing includes initialization, state detection and insulation layer repair. The initialization step ensures that the initial state of each storage cell is consistent to facilitate subsequent write operations. The state detection step detects the current state of the storage cell through built-in sensors, such as temperature, voltage, current and other physical parameters to evaluate whether it is suitable for writing. If it is detected that the storage cell is faulty or the insulation layer is damaged, the insulation layer repair step will be performed. The insulation layer repair can be performed by heat treatment or chemical treatment to restore the insulation performance of the storage cell. It can be understood that the preprocessing step can improve the stability of the write process and reduce the write failure rate due to poor state of the storage cell.

[0024] Furthermore, the optimal write parameters are determined by an adaptive quantum tunneling algorithm. The algorithm dynamically adjusts the voltage and current according to the current state and environmental conditions of the solid-state storage device to optimize the write speed. Specifically, the adaptive quantum tunneling algorithm first collects the current state data of the solid-state storage device, such as environmental parameters such as temperature, humidity, voltage, and current. Then, by analyzing this data, the algorithm dynamically adjusts the frequency and amplitude of the pulse voltage to adapt to the current writing conditions. It should be understood that the adaptive quantum tunneling algorithm not only takes into account the internal state of the storage device, but also the influence of the external environment, thereby ensuring efficient data writing under various conditions.

[0025] Furthermore, parallel quantum tunneling is used to write to multiple storage cells at the same time. Each storage cell is independently controlled to reduce write latency. By writing in parallel, more data can be processed in the same write time, significantly improving the write speed. Specifically, the controller inside the solid-state storage device is responsible for allocating and managing the write operations of each storage cell. The controller of each storage cell independently applies a pulse voltage to achieve data writing according to the optimal parameters determined by the adaptive quantum tunneling algorithm. It can be understood that parallel quantum tunneling not only improves the write speed, but also reduces write failures caused by single point failures.

[0026] Furthermore, the writing process is monitored and fed back in real time. The motion state of electrons and the physical properties of the storage unit, such as temperature, voltage, and current, are detected by built-in sensors during the writing process. The real-time monitoring data is transmitted to the adaptive quantum tunneling algorithm through the controller, and the algorithm dynamically adjusts the writing parameters based on these data to ensure the stability and efficiency of the writing process. It should be understood that the real-time monitoring and feedback mechanism can promptly detect and correct anomalies in the writing process, thereby reducing the risk of writing failures and improving the reliability of data writing.

[0027] Furthermore, a verification algorithm is used to verify the data written to the solid-state storage device to ensure the integrity of the data. After the write operation is completed, the verification algorithm verifies the written data to ensure that the data is not lost or damaged. Specifically, the verification algorithm can use common data verification methods such as CRC (cyclic redundancy check) or ECC (error correction code). If a data error is detected, the verification algorithm will trigger a data rewrite mechanism to ensure the integrity of the data written. It can be understood that the use of the verification algorithm can further improve the reliability of data writing and ensure that no data is lost or damaged during the writing process.

[0028] Through this embodiment, high-speed and low-power data writing of solid-state storage devices can be achieved. Specifically, by accurately controlling pulse voltage parameters, preprocessing steps, adaptive quantum tunneling algorithms, parallel quantum tunneling, real-time monitoring and feedback mechanisms, and data verification algorithms, the entire writing process is optimized. This embodiment not only improves the writing speed, but also reduces power consumption and improves the reliability of data writing. Efficient and reliable data writing can be achieved under a wide range of environmental conditions to meet the needs of high-performance solid-state storage devices.

[0029] Embodiment 2 In order to solve the problem of excessive heat generation and low quantum tunneling efficiency when solid-state storage devices generate quantum tunneling conditions, this embodiment further optimizes the steps of achieving quantum tunneling through high-frequency, low-amplitude pulse voltages. By precisely controlling the pulse voltage parameters, heat generation during the writing process is reduced, while the quantum tunneling efficiency is improved, thereby achieving low power consumption and efficient writing operations.

[0030] First, a high-frequency, low-amplitude pulse voltage is applied across the storage unit of the solid-state storage device. Specifically, the frequency range of the pulse voltage is set to 100 MHz to 200 MHz, and the amplitude range is set to 0.5 V to 1.5 V. The selection of these parameters is based on the physical properties of the quantum tunneling effect and the material properties of the storage unit. High-frequency pulses can reduce the heat generated by electrons during the tunneling process, while low-amplitude pulses can ensure tunneling efficiency while avoiding damage to the storage unit caused by excessive voltage. It should be understood that the combination of high-frequency and low-amplitude pulse voltages can effectively balance heat generation and tunneling efficiency, thereby achieving fast data writing under low power consumption conditions.

[0031] Furthermore, the pulse parameters are dynamically adjusted by an adaptive pulse adjustment algorithm to ensure that quantum tunneling conditions are generated quickly and stably. The specific expression of the adaptive pulse adjustment algorithm is: , where V(t) is the pulse voltage, V0 is the reference voltage, and a n and b n is the amplitude parameter, f n and g n is the frequency parameter, ϕ n and δ n are phase parameters. These parameters are adjusted in real time according to the material properties of the storage unit and the ambient temperature. It can be understood that the adaptive pulse adjustment algorithm dynamically adjusts the pulse parameters to ensure that stable quantum tunneling conditions can be generated under different environmental conditions, thereby improving the writing speed.

[0032] Furthermore, the adaptive pulse adjustment algorithm will make real-time adjustments based on the physical characteristics of the storage unit when generating quantum tunneling conditions. Specifically, the built-in sensor will detect the environmental parameters such as temperature, humidity, and voltage of the storage unit in real time, and transmit this data to the adaptive pulse adjustment algorithm. Based on this data, the algorithm uses the amplitude parameter a in the formula n and b n , frequency parameter f n and g n , phase parameter φ n and δ n Adjustment to ensure that the waveform and intensity of the pulse voltage are always in the best state, such as Figure 3 It should be understood that this real-time adjustment mechanism can respond to environmental changes in a timely manner, maintain optimal tunneling conditions, and reduce the write failure rate caused by environmental changes.

[0033] Furthermore, the adaptive pulse adjustment algorithm can be implemented in a variety of ways in practical applications. For example, the algorithm can be embedded in the controller of the storage device, and the pulse voltage parameters can be calculated and adjusted in real time through the digital signal processor (DSP). The controller communicates with the sensor of the storage unit to obtain real-time data and adjusts the pulse voltage generation circuit according to the optimal parameters output by the algorithm. It can be understood that this embedded implementation can improve the execution efficiency of the algorithm, reduce data transmission delays, and ensure the timeliness and accuracy of write operations.

[0034] Through this embodiment, high-frequency, low-amplitude pulse voltage application can be achieved in solid-state storage devices to generate efficient quantum tunneling conditions. Specifically, by using an adaptive pulse adjustment algorithm, the pulse voltage parameters are adjusted in real time according to the physical characteristics of the storage unit, and fast and stable data writing can be achieved while maintaining low power consumption. Heat generation during the writing process is reduced, and quantum tunneling efficiency is improved.

[0035] Embodiment 3 In order to solve the problem of write failure caused by charge accumulation and insulation layer damage during the pre-processing of solid-state storage devices, this embodiment further optimizes the steps of pre-processing the storage unit. Through charge balancing, real-time detection and charge trap repair, it is ensured that each storage unit is in a state suitable for writing, thereby improving the stability and reliability of the writing process.

[0036] In this embodiment, the memory cell is firstly charged and balanced. Specifically, by applying a reverse voltage, the charge accumulation in the memory cell is eliminated to ensure that each memory cell is in the same initial state. It is understandable that charge accumulation will cause the potential difference between the memory cells to increase, thereby affecting the tunneling efficiency of electrons and the accuracy of data writing. The application time of the reverse voltage can be set to 100 μs to 200 μs, and the voltage range is -0.5 V to -1.5 V to ensure thorough and efficient charge balancing.

[0037] Furthermore, a detector is used to detect the state parameters of the storage unit in real time. The state parameters include the resistance value, capacitance value and temperature value of the storage unit. The detector can use a high-precision resistance meter, capacitance meter and temperature sensor to detect the resistance value, capacitance value and temperature value of the storage unit respectively. These data will be transmitted to the controller in real time for evaluating the current state of the storage unit. It should be understood that real-time detection can promptly detect the failure or abnormality of the storage unit, provide accurate data support for subsequent adjustment and repair, thereby improving the reliability of the writing process.

[0038] Furthermore, the insulating layer of the storage unit is repaired for charge traps. Specifically, a laser beam is used to scan the insulating layer to eliminate trapped charges to improve tunneling efficiency. The scanning speed of the laser beam can be adjusted according to the material properties of the insulating layer, and is usually set to 1 μm / s to 5 μm / s. It should be understood that trapped charges will reduce the tunneling efficiency of the insulating layer and increase power consumption and failure rate during writing. By scanning with a laser beam, these trapped charges can be effectively eliminated and the performance of the insulating layer can be restored.

[0039] Furthermore, during the charge trap repair process, a feedback control algorithm is used to adjust the laser parameters according to the laser beam scanning results. Specifically, the expression of the feedback control algorithm is: , where I laser (t) is the laser current, P target is the target power, P actual (t) is the actual power, R unit (t) is the resistance value of the memory cell, T unit (t) is the temperature value of the storage unit, and k1 and k2 are coefficients adjusted according to the material characteristics of the insulation layer. It should be understood that the feedback control algorithm ensures that the power and scanning effect of the laser beam are always in the best state by adjusting the laser current in real time, thereby improving the efficiency and accuracy of the insulation layer repair.

[0040] Through this embodiment, charge balancing, real-time detection, and charge trap repair of solid-state storage devices during preprocessing can be achieved. Specifically, charge accumulation is eliminated by reverse voltage, the state parameters of the storage unit are detected in real time by a high-precision detector, the insulating layer trap charge is repaired by laser beam scanning, and the laser parameters are dynamically adjusted by a feedback control algorithm to ensure that each storage unit is in a state suitable for writing. The benefit of this embodiment is that it improves the efficiency and reliability of the preprocessing step, reduces the failure rate during the writing process, and improves the stability and accuracy of data writing.

[0041] Embodiment 4 In order to solve the problem of inaccurate parameter adjustment and insufficient adaptability of solid-state storage devices in the adaptive quantum tunneling algorithm, this embodiment further optimizes the adaptive quantum tunneling algorithm. By evaluating the state of the storage unit before writing and updating the machine learning model in real time during the writing process, it is ensured that the writing parameters are always in the optimal state, thereby achieving efficient data writing.

[0042] First, before writing, the machine learning model input includes the resistance value, capacitance value, temperature value and previously written data features of the storage unit to evaluate the current state of the solid-state storage device and obtain an evaluation result. Specifically, the machine learning model can use a deep neural network (DNN) or other suitable models. The input data features include the current resistance value, capacitance value, temperature value of the storage unit and the previously written data features, such as the number of writes, the type of written data, etc. It can be understood that these input data can fully reflect the current state of the storage unit and provide an accurate evaluation basis for the adaptive quantum tunneling algorithm.

[0043] Furthermore, the write parameters are dynamically adjusted according to the evaluation results. The specific steps include: calculating the feature vector x of the current state; using the pre-trained neural network model f for prediction and outputting the optimal write parameter y. The calculation expression of the optimal write parameter y is: , where A is the feature weight matrix, B is the bias vector, C is the correction weight matrix, and D is the correction bias vector. These parameters are obtained through the pre-trained neural network model and can accurately reflect the current state of the storage unit. It should be understood that through the combination of the feature vector x and the neural network model f, the optimal write parameters can be accurately predicted, thereby improving the efficiency and reliability of the write process.

[0044] Furthermore, during the writing process, the machine learning model is updated in real time to adapt to the dynamic changes of the storage device. Specifically, the controller collects the write status data of the storage unit in real time, such as write voltage, write current, write time, etc., and uses these data to update the machine learning model. The update of the machine learning model can embed an online learning module in the controller to continuously optimize the parameters of the model through incremental learning. It can be understood that this real-time update mechanism can ensure that the machine learning model always adapts to the current state of the storage device and improves the accuracy and adaptability of the adaptive quantum tunneling algorithm.

[0045] Through this embodiment, efficient and low-power data writing of solid-state storage devices can be achieved. Specifically, the current state of the storage unit is evaluated through a machine learning model, and the writing parameters are dynamically adjusted. The machine learning model is updated in real time during the writing process to ensure that the optimal writing parameters can be achieved under various conditions. The accuracy and adaptability of the adaptive quantum tunneling algorithm are improved, the failure rate during the writing process is reduced, and the writing speed and reliability of the solid-state storage device are improved.

[0046] Embodiment 5 In order to solve the problem of low efficiency and write delay in the parallel quantum tunneling writing process of solid-state storage devices, this embodiment further optimizes the steps of using parallel quantum tunneling to write multiple storage units at the same time. By using multi-core control circuits, time division multiplexing technology and dynamic optimal write order calculation, it is ensured that each storage unit can achieve efficient data writing under independent control and synchronous writing conditions, such as Figure 4 shown.

[0047] First, a multi-core control circuit is used to write to multiple storage cells simultaneously. The design of the multi-core control circuit adopts a highly parallel processing architecture, and each core is independently responsible for the writing operation of a storage cell, thereby achieving a synchronous and independent writing process.

[0048] Furthermore, time division multiplexing technology is used to decompose the write operation into multiple time slices, and a group of storage units are written in each time slice. Time division multiplexing technology achieves efficient management of data writing by allocating write operations to different time slices. Specifically, the controller dynamically adjusts the number and order of storage units written in each time slice according to the number of storage units and the write capacity of each time slice. It can be understood that time division multiplexing technology can effectively balance the write time of each storage unit, reduce global write latency, and improve overall write efficiency.

[0049] Furthermore, the optimal write order for each time slice is calculated using the following expression: , where s represents the optimal write order, is an index vector of a storage unit, represents the order of writing units in each time slice, s' represents the candidate write order, represents the possible write order, argmax s' represents the candidate write order s' that makes the f(s') value the largest, n represents the total number of storage units, i represents the i-th storage unit, d s'(i) represents the distance from the i-th storage unit to the control circuit, R s'(i) represents the resistance value of the i-th storage unit, C s'(i) represents the capacitance value of the i-th storage unit, log(1+C s'(i) ) represents taking the logarithm of the capacitance value and adding 1 to avoid the situation where the denominator is 0 and balance the influence of the capacitance value. It can be understood that this dynamic optimal write order calculation method can achieve efficient data write order according to the specific physical characteristics of the storage unit and reduce conflicts and delays in the write process.

[0050] Furthermore, in order to ensure the accuracy and efficiency of calculations, the controller can use a high-performance mathematical unit (FPU) and an optimized algorithm library. Specifically, the FPU can accelerate floating-point operations and increase the calculation speed; the optimized algorithm library can provide efficient mathematical function implementation and reduce the consumption of computing resources. It can be understood that through the combination of hardware and software optimization, the efficiency of the optimal write order calculation can be significantly improved, ensuring the real-time and accuracy of the write process.

[0051] Furthermore, the controller is also equipped with high-speed data transmission interfaces, such as PCIe 4.0 and DDR4 or DDR5 memory interfaces, to support high-speed data reading, writing and transmission. These interfaces can significantly increase the data transmission rate, reduce data transmission delays, and ensure efficient write operations. It should be understood that high-speed data transmission interfaces are an important support for achieving efficient parallel writing, which can ensure the rapid transfer and synchronous writing of data between various storage units.

[0052] Through this embodiment, the writing efficiency of the solid-state storage device can be improved. Specifically, the multi-core control circuit realizes parallel processing and independent control, the time division multiplexing technology balances the writing time of each storage unit, and the dynamic optimal writing order calculation optimizes the writing order according to the physical characteristics of the storage unit. The comprehensive application of these technologies ensures that efficient data writing can be achieved under various conditions. The parallelism and real-time performance of the write operation are improved, the write delay is reduced, and the writing performance of the solid-state storage device is improved.

[0053] Embodiment 6 In order to solve the problem of insufficient accuracy and low verification efficiency of solid-state storage devices during data verification, this embodiment further optimizes the step of using a verification algorithm to verify written data. Data verification is performed through the motion state of electrons during quantum tunneling, and a multi-level verification algorithm is used to verify the low-level and high-level features of the data respectively, thereby ensuring the integrity and accuracy of the data.

[0054] First, data verification is performed through the motion state of electrons during quantum tunneling. Specifically, the built-in sensor detects the motion state of electrons during tunneling in real time, including the energy level changes, tunneling time, tunneling current, etc. of electrons. These data will be transmitted to the verification algorithm to evaluate the correctness of data writing. It should be understood that the detection of the motion state of electrons can provide direct feedback on the writing process, which helps to detect anomalies in the writing process in a timely manner and improve the accuracy of verification.

[0055] Furthermore, a multi-level verification algorithm is used to verify the low-level and high-level features of the data respectively. The multi-level verification algorithm includes physical layer verification, logical layer verification and application layer verification. The physical layer verification mainly focuses on the physical characteristics of the storage unit, such as voltage, current and temperature; the logical layer verification mainly focuses on the logical structure of the data, such as the error rate and checksum of the data block; the application layer verification mainly focuses on the application layer characteristics of the data, such as data hash value and check strength. It can be understood that the independent operation and mutual verification of the multi-level verification algorithm can comprehensively cover all aspects of data verification and ensure the integrity and accuracy of the data.

[0056] Furthermore, the specific steps of the physical layer verification are as follows: Calculate the low-level feature vector F1 of each storage unit, where F1 includes physical parameters such as voltage, current and temperature of the storage unit. Use the following expression for physical layer verification: , where A is the low-level feature weight matrix, B is the high-level feature weight matrix, C is the temperature weight matrix, and T is the temperature vector. It can be understood that the physical layer verification can detect physical layer anomalies in a timely manner and improve the accuracy of data verification by comprehensively considering the physical characteristics of the storage unit.

[0057] Furthermore, the specific steps of the logic layer verification are as follows: Calculate the high-level feature vector F2 of each logic block, where F2 includes logic parameters such as the data type, data length and check code of the logic block. Use the following expression for logic layer verification: ,It is understandable that the logic layer verification can ,promptly discover anomalies at the logic level and improve the ,reliability of data verification by comprehensively considering the ,logical structure of data.

[0058] Furthermore, the specific steps of the application layer verification are as follows: calculate the low-level feature vector F1 and the high-level feature vector F2 of each application layer data block, and use the temperature vector T for comprehensive verification. The specific expression is also: , where A, B and C are low-level feature weight matrix, high-level feature weight matrix and temperature weight matrix respectively. These weight matrices can be adjusted according to the actual situation of the storage device to optimize the verification effect. It should be understood that application layer verification can provide a higher level of verification guarantee by comprehensively considering the application layer characteristics of the data to ensure the integrity of the data at the application layer.

[0059] Furthermore, in order to improve the execution efficiency of the verification algorithm, a high-performance mathematical unit (FPU) and an optimized algorithm library can be embedded in the controller. Specifically, the FPU can accelerate floating-point operations and increase the verification speed; the optimized algorithm library can provide efficient mathematical function implementation and reduce the consumption of computing resources. It can be understood that through the combination of hardware and software optimization, the execution efficiency of the multi-level verification algorithm can be significantly improved to ensure the timeliness and accuracy of data verification.

[0060] Through this embodiment, the data verification accuracy and efficiency of the solid-state storage device can be improved. Specifically, by verifying the data through the motion state of electrons in the quantum tunneling process, and using a multi-level verification algorithm to verify the low-level and high-level features of the data respectively, all aspects of data verification can be fully covered to ensure the integrity and accuracy of the data.

[0061] Embodiment 7 In order to solve the problem of reduced data writing efficiency and reduced data reliability caused by excessively high temperatures in solid-state storage devices during the writing process, this embodiment further optimizes the method of using low-temperature cooling to maintain the temperature range of the storage unit during the writing process. Through the combination of active cooling and passive cooling, as well as the calculation of the dynamic optimal cooling power, it is ensured that the temperature of the storage unit is always in the optimal range during the writing process, thereby improving the writing speed and data reliability of quantum tunneling.

[0062] First, cryogenic cooling is used to maintain the temperature range of the storage unit during the writing process. Specifically, the cryogenic cooling system consists of two parts: active cooling and passive cooling. The active cooling system is controlled by a micro-cooling system, and the passive cooling system is implemented through heat dissipation materials and structural design. It should be understood that the active cooling system can adjust the cooling power in real time during the writing process to ensure the stability of the temperature, such as Figure 5 As shown; the passive cooling system provides continuous heat dissipation and reduces temperature fluctuations through heat dissipation materials and structural design.

[0063] Furthermore, the active cooling system calculates the optimal cooling power using the following expression: , where P cool is the cooling power, T current is the current temperature, T target is the target temperature, V write is the write voltage, I write is the write current, and k3 is the adjustment coefficient. It can be understood that the calculation method of the optimal cooling power can dynamically adjust the cooling power by comprehensively considering the current temperature, target temperature and write parameters of the storage unit to ensure that the temperature of the storage unit is always in the optimal range.

[0064] Furthermore, the passive cooling system can be realized by selecting high-performance heat dissipation materials and optimizing the structural design. Specifically, the heat dissipation material can use materials such as metal alloys or graphene with high thermal conductivity, and the structural design can improve the heat dissipation effect through micro heat sinks or heat dissipation channels. It should be understood that high-performance heat dissipation materials and optimized structural design can significantly improve the heat dissipation effect of the storage unit, reduce temperature fluctuations, and ensure the stability of the writing process.

[0065] Furthermore, the controller monitors the temperature changes of the storage unit in real time and adjusts the parameters of the low-temperature cooling system according to the temperature changes. Specifically, the controller obtains the temperature data of the storage unit in real time through the built-in temperature sensor and transmits this data to the optimal cooling power calculation algorithm. The algorithm dynamically adjusts the power of the cooling system based on this data to ensure that the temperature is always in the optimal range. It can be understood that the real-time monitoring and adjustment mechanism can respond to temperature changes in a timely manner, reduce the impact of temperature fluctuations on the writing process, and improve writing efficiency and data reliability.

[0066] Furthermore, in order to improve the execution efficiency of the cooling system, a high-performance mathematical unit (FPU) and an optimized algorithm library can be embedded in the controller. Specifically, the FPU can accelerate floating-point operations and increase the speed of cooling power calculation; the optimized algorithm library can provide efficient mathematical function implementation and reduce the consumption of computing resources. It can be understood that through the combination of hardware and software optimization, the execution efficiency of the cooling system can be significantly improved, ensuring the real-time and accuracy of the cooling process.

[0067] Through this embodiment, efficient low-temperature cooling can be achieved during the writing process of the solid-state storage device, keeping the temperature of the storage unit always in the optimal range. Specifically, through the combination of active cooling and passive cooling, and the calculation of the dynamic optimal cooling power, the impact of temperature fluctuations on data writing can be significantly reduced, and the writing speed can be improved. Through the comprehensive application of multiple cooling technologies, the temperature stability of the writing process is ensured, and the writing efficiency of quantum tunneling is improved.

[0068] Embodiment 8 In order to solve the problem of low data writing efficiency and reduced reliability caused by uneven wear of storage units in the writing process of solid-state storage devices, this embodiment further optimizes the step of performing wear leveling processing on the storage units of the storage device before writing, such as Figure 6 By calculating the wear level of each storage unit and using the wear leveling algorithm to redistribute the written data, the wear level of each unit is ensured to be uniform, thereby improving the reliability and efficiency of data writing.

[0069] First, before writing, the storage unit of the storage device is wear-leveled. Specifically, by calculating the wear level W of each storage unit i To assess its current wear status. Wear degree W i A comprehensive evaluation can be performed through parameters such as the number of writes, write voltage, write current, etc. It can be understood that the calculation of the wear degree can fully reflect the wear condition of the storage unit and provide an accurate basis for wear leveling processing.

[0070] Furthermore, a wear leveling algorithm is used to redistribute the written data. Specifically, the wear leveling algorithm aims to make the wear of each storage unit as uniform as possible by redistributing data. The expression of the algorithm is: , where D new is the redistributed data matrix, D old is the original data matrix, W is the wear degree matrix, and A and B are adjustment matrices. It should be understood that this expression can dynamically adjust the data allocation strategy by introducing the wear degree matrix W and the adjustment matrices A and B, so that the storage cells with lower wear degree are given priority to write data, thereby achieving wear leveling.

[0071] Furthermore, the specific implementation of the wear leveling algorithm can be performed in the controller. The controller can use a high-performance embedded processor, such as the NXP i.MX 8QuadXPlus, equipped with 4 GB LPDDR4 memory and 32 GB eMMC storage to support efficient wear leveling processing. It should be understood that a high-performance embedded processor can handle complex wear leveling algorithms to ensure the efficiency and accuracy of data allocation.

[0072] Furthermore, the wear leveling algorithm also takes into account the physical characteristics and current working status of the storage unit. Specifically, the controller monitors parameters such as temperature, voltage, and current of each storage unit in real time and incorporates this data into the wear leveling calculation. For example, a storage unit with a higher temperature may be cooled first instead of writing data immediately to reduce the impact of high temperature on the writing process. It can be understood that by comprehensively considering the physical characteristics and the current working status, the wear leveling algorithm can more comprehensively optimize the data writing strategy and ensure that the writing process of each storage unit is more stable and reliable.

[0073] Furthermore, wear leveling processing can also be combined with multi-core control circuits and time-division multiplexing technology to further optimize the writing process. Specifically, the multi-core control circuit can process the wear degree calculation and data allocation of multiple storage units in parallel, and the time-division multiplexing technology can decompose the data allocation and writing process into multiple time slices, completing a part of the wear leveling and data writing in each time slice. It should be understood that this combination can give full play to the parallel advantages of multi-core processing and the time management advantages of time-division multiplexing, further improving writing efficiency and data reliability.

[0074] Through this embodiment, efficient wear leveling processing can be implemented during the writing process of the solid-state storage device. Specifically, by calculating the degree of wear of each storage unit and using the wear leveling algorithm to redistribute the written data, it is ensured that the degree of wear of each storage unit is uniform, thereby improving the reliability and efficiency of data writing. The benefit of this embodiment is that through wear leveling processing, the service life of the storage device can be extended, the performance degradation and data reliability reduction caused by uneven wear can be reduced, and the overall writing performance and storage stability can be improved.

[0075] Embodiment 9 In order to solve the problem of insufficient data reliability and high writing error rate caused by a single verification mechanism during data writing of solid-state storage devices, this embodiment further optimizes the steps of adopting a multi-layer data verification mechanism. Through the comprehensive application of physical layer verification, logical layer verification and application layer verification, multi-faceted verification of data is ensured to improve the reliability of writing.

[0076] First, a multi-layer data verification mechanism is used to improve the reliability of writing by verifying data in many aspects. The multi-layer data verification mechanism includes physical layer verification, logical layer verification and application layer verification. Each layer of verification algorithm runs independently and verifies each other. Figure 7 As shown, thus ensuring the completeness and accuracy of the data at different levels.

[0077] Furthermore, the physical layer checksum uses the following expression to calculate the checksum value: , where C phy is the physical layer check value, V i is the voltage vector of the i-th storage unit, I i is the current vector of the i-th storage unit, T i is the temperature vector of the i-th storage unit, and N is the total number of storage units. It can be understood that the physical layer verification can timely detect physical layer anomalies and improve the accuracy of data verification by comprehensively considering physical parameters such as voltage, current and temperature of the storage unit.

[0078] Furthermore, the logic layer checksum uses the following expression to calculate the checksum value: , where C log is the logic layer checksum, D i is the data vector of the i-th logic block, W i is the weight vector of the i-th logic block, R log,i is the error rate of the ith logic block, and M is the total number of logic blocks. It can be understood that the logic layer verification can timely detect the abnormality of the logic layer and improve the reliability of data verification by comprehensively considering the logical structure and error rate of the data.

[0079] Furthermore, the application layer checksum uses the following expression to calculate the checksum value: , where C app is the application layer checksum value, H j is the data hash vector of the jth application layer, S j is the check code vector of the jth application layer, Q app,j is the verification strength of the jth application layer, and K is the total number of application layer data blocks. It can be understood that the application layer verification can provide a higher level of verification assurance by comprehensively considering the application layer characteristics of the data, such as data hash value and verification strength, to ensure the integrity of the data at the application layer.

[0080] Furthermore, the independent operation and mutual verification of the multi-layer verification mechanism can ensure the comprehensiveness and reliability of data verification. Specifically, the physical layer verification, logical layer verification and application layer verification can be run independently in different time slices, and each verification result will be transmitted to the controller for verification and integration. It should be understood that this independent operation and mutual verification mechanism can fully cover all aspects of data verification and ensure the integrity and accuracy of data at different levels.

[0081] Furthermore, the multi-layer verification mechanism can also be combined with a cryogenic cooling system and wear leveling processing to further optimize the writing process. Specifically, the cryogenic cooling system can keep the temperature of the storage unit stable during the writing process, reducing the impact of high temperature on the writing process; wear leveling processing can ensure that the degree of wear of each storage unit is uniform, extending the service life of the storage device. It can be understood that through the combination of a multi-layer verification mechanism with cryogenic cooling and wear leveling processing, the reliability of data writing can be significantly improved, the write error rate can be reduced, and the overall performance of solid-state storage devices can be improved.

[0082] The benefit of this embodiment is that through the comprehensive application of a multi-layer data verification mechanism, all aspects of data verification can be fully covered to ensure the integrity and accuracy of data at the physical layer, logical layer and application layer. Specifically, the physical layer verification focuses on the physical characteristics of the storage unit, the logical layer verification focuses on the logical structure of the data, and the application layer verification focuses on the application layer characteristics of the data. This multi-layer verification mechanism can improve the accuracy of the verification, reduce data errors during the writing process, and improve the writing performance of the solid-state storage device.

[0083] Embodiment 10 In order to solve various problems that solid-state storage devices may encounter during high-speed writing, such as high-precision voltage control, storage unit preprocessing, adaptive writing parameter adjustment, parallel writing, real-time monitoring, data verification, low-temperature cooling and wear leveling, this embodiment further optimizes various modules of the high-speed writing system. Through the comprehensive design of the system, the efficiency, accuracy and reliability of data writing are ensured.

[0084] First, the writing system includes a high-precision voltage generation module, which is implemented by using a high-precision voltage controller to generate pulse voltage under quantum tunneling conditions. Specifically, the voltage generation module can use ADI's AD5791 high-precision DAC (digital-to-analog converter), which has an accuracy of up to 16 bits and an output voltage range of -10 V to +10 V. It should be understood that high-precision voltage control can ensure that the voltage pulses during quantum tunneling are accurate and stable, thereby improving the accuracy and reliability of the writing operation.

[0085] Furthermore, the design of the pre-processing module includes functions such as charge balancing, state detection and insulation layer repair, which are used to pre-process the storage unit. The charge balancing function is implemented by using a charge pump circuit to ensure that the charge distribution of the storage unit before writing is uniform. The state detection function monitors the current state of the storage unit in real time through built-in sensors, such as voltage, current and temperature, so as to adjust the pre-processing parameters in time. The insulation layer repair function repairs the insulation layer of the storage unit by using nano-scale repair materials and technologies to ensure its stable performance. It can be understood that the comprehensive functions of the pre-processing module can significantly improve the readiness of the storage unit and ensure the smooth progress of the write operation.

[0086] Furthermore, the adaptive quantum tunneling algorithm module is used to dynamically adjust the write parameters according to the current state and environmental conditions of the storage device. Specifically, the adaptive algorithm module can collect the current, voltage, temperature and other data of the storage device in real time through the controller, and dynamically adjust the write voltage and write time according to these data. The algorithm module can use the ARM Cortex-A72 processor in the embedded system, with a processing speed of up to 1.5 GHz and equipped with 4 GB DDR4 memory to support efficient adaptive algorithm processing. It should be understood that the dynamic adjustment capability of the adaptive algorithm module can ensure that the parameters of the write operation are always in the best state under different environmental conditions, improving write efficiency and data reliability.

[0087] Furthermore, the parallel write module writes to multiple storage units at the same time through a multi-core control circuit, realizes parallel quantum tunneling, and supports high parallel processing. Each core is independently responsible for the write operation of a storage unit, and the write speed is significantly improved through parallel processing. It can be understood that the high parallel processing capability of the parallel write module can significantly reduce the write time and ensure stable performance when writing a large amount of data.

[0088] Furthermore, the real-time monitoring module uses sensors to detect the electron motion state and physical properties of the storage unit during the writing process, and provides real-time feedback. Specifically, the real-time monitoring module can use highly sensitive Hall effect sensors and thermocouple sensors to monitor the electron motion state and temperature changes, respectively. The sensor data is transmitted to the controller through a high-speed interface, and the controller adjusts the writing parameters in real time based on these data. It should be understood that the high-precision sensors of the real-time monitoring module can detect abnormal conditions during the writing process in a timely manner, ensuring the accuracy and stability of the writing operation.

[0089] Furthermore, the data verification module uses self-verification based on quantum tunneling to ensure that the data is complete and accurate. Specifically, the data verification module can perform real-time verification through the state of electron motion during quantum tunneling, and verify the low-level and high-level features of the data in combination with a multi-level verification algorithm. For example, low-level features include physical parameters such as voltage, current, and temperature, and high-level features include logical parameters such as data type, data length, and check code. It can be understood that self-verification based on quantum tunneling can provide real-time feedback and improve the accuracy and reliability of verification.

[0090] Furthermore, the cryogenic cooling module maintains the temperature of the storage unit within the optimal range through active cooling and passive cooling technology, thereby improving the stability of quantum tunneling. Specifically, the active cooling system can use a micro Peltier cooler to adjust the cooling power in real time through a controller to keep the temperature within the target range. The passive cooling system can use high-performance graphene heat dissipation materials and optimized heat dissipation structure designs, such as microchannel radiators, to provide continuous heat dissipation effects. It should be understood that the dual cooling technology of the cryogenic cooling module can ensure the temperature stability of the storage unit during the writing process and reduce the impact of high temperature on writing performance.

[0091] Furthermore, the wear leveling module performs wear leveling on the storage unit to ensure that the wear degree of each unit is uniform and prolong the life of the storage device. Specifically, the wear leveling module can calculate the wear degree of each storage unit through the controller and use the wear leveling algorithm to redistribute the written data.

[0092] Furthermore, the multi-layer data verification mechanism module improves the reliability of data writing through multi-layer verification of the physical layer, logical layer and application layer. Specifically, the physical layer verification is performed by calculating the physical layer verification value of each storage unit, the logical layer verification is performed by calculating the logical layer verification value of each logical block, and the application layer verification is performed by calculating the verification value of each application layer data block. It should be understood that the independent operation and mutual verification of the multi-layer data verification mechanism can fully cover all aspects of data verification and ensure the integrity and accuracy of data at different levels.

[0093] Furthermore, the communication interface module supports multiple data transmission protocols to achieve efficient communication with external devices. Specifically, the communication interface module can support multiple high-speed data transmission protocols such as PCIe 4.0, DDR4, SATA 3.0 and USB 3.2 to ensure high speed and low latency of data transmission. It should be understood that the support of multiple high-speed data transmission protocols can improve the flexibility and reliability of data transmission and ensure the efficient operation of the write system.

[0094] Furthermore, the power management module provides power supply and energy optimization for the write system. Specifically, the power management module should support a wide input voltage range and high-efficiency output. In addition, the power management module can also dynamically adjust the power consumption of the system through an intelligent power management algorithm to ensure the stability and efficiency of the system under high load conditions. It can be understood that efficient power management and dynamic power consumption adjustment can reduce system energy consumption and improve the overall performance and reliability of the system.

[0095] Through this embodiment, high-precision voltage control, comprehensive preprocessing, adaptive write parameter adjustment, parallel writing, real-time monitoring, multi-layer data verification, low-temperature cooling and wear leveling and other optimizations can be achieved during the high-speed writing process of solid-state storage devices. Specifically, the high-precision voltage generation module ensures the accuracy and stability of the voltage pulse during quantum tunneling; the preprocessing module improves the readiness of the storage unit through charge balancing, state detection and insulation layer repair; the adaptive quantum tunneling algorithm module dynamically adjusts the write parameters according to the current state and environmental conditions to ensure the efficiency of the write operation; the parallel write module realizes parallel processing through a multi-core control circuit to improve the write speed; the real-time monitoring module uses high-precision sensors to provide real-time feedback to ensure the accuracy and stability of the write operation; the data verification module adopts self-verification and multi-level verification algorithms based on quantum tunneling to improve the reliability and accuracy of data verification; the low-temperature cooling module maintains temperature stability through active cooling and passive cooling technology to improve the stability of quantum tunneling; the wear leveling module reduces uneven wear of storage units and extends the service life of the equipment through dynamic data allocation strategies; the communication interface module supports multiple high-speed data transmission protocols to improve the flexibility of data transmission; the power management module reduces system energy consumption and improves overall performance through efficient power management and dynamic power consumption adjustment.

[0096] The benefit of this embodiment is that, through the comprehensive design of the system, the efficiency, accuracy and reliability of the solid-state storage device during high-speed writing are ensured. Specifically, the various modules of the system cooperate with each other to form a complete and optimized data writing process, which can improve the speed and accuracy of data writing, reduce the error rate, extend the service life of the device, and improve the overall performance and stability. Through this embodiment, the high-speed writing system of the solid-state storage device can operate stably under various environmental conditions to meet the needs of high data throughput and high speed.

[0097] The above embodiments further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the present invention should be included in the scope of protection of the present invention.

Claims

1. A high-speed writing method for a solid-state storage device, characterized in that: The writing method comprises the following steps: Applying a specific pulse voltage across the storage unit of the solid-state storage device to enable electrons to quantum tunnel through the insulating layer, thereby generating quantum tunneling conditions for writing data with low power consumption; Preprocessing the storage unit, wherein the preprocessing steps include initialization, state detection and insulation layer repair, to ensure that each storage unit is in a state suitable for writing; determining optimal write parameters by an adaptive quantum tunneling algorithm that dynamically adjusts voltage and current according to a current state and environmental conditions of the solid-state storage device to optimize write speed; Using parallel quantum tunneling to write to multiple storage cells simultaneously, each storage cell is independently controlled to reduce write delay; Real-time monitoring and feedback of the writing process are performed, the motion state of the electrons and the physical properties of the storage unit during the writing process are detected by built-in sensors, and the writing parameters are adjusted according to the feedback results; The data written to the solid-state storage device is verified using a verification algorithm to ensure the integrity of the data.

2. The high-speed writing method for a solid-state storage device according to claim 1, characterized in that: The step of generating quantum tunneling conditions comprises: Applying a high-frequency, low-amplitude pulse voltage across the storage unit to reduce heat generation during writing and improve quantum tunneling efficiency; Adjusting pulse parameters, wherein the pulse parameters include a frequency range and an amplitude range, wherein the frequency range is adjusted to 100 MHz to 200 MHz, and the amplitude range is adjusted to 0.5 V to 1.5 V, and by controlling the pulse parameters, quantum tunneling conditions are generated quickly and stably; When generating the quantum tunneling condition, an adaptive pulse adjustment algorithm is used. The adaptive pulse adjustment algorithm dynamically adjusts the frequency range and the amplitude range according to the physical characteristics of the storage unit. The adaptive pulse adjustment algorithm is expressed as: , where V(t) is the pulse voltage, V0 is the reference voltage, and a n and b n is the amplitude parameter, f n and g n is the frequency parameter, ϕ n and δ n is the phase parameter.

3. The high-speed writing method for a solid-state storage device according to claim 1, characterized in that: The step of preprocessing the storage unit comprises: Performing charge balancing on the storage cells, eliminating charge accumulation in the storage cells by applying a reverse voltage, so as to ensure that each of the storage cells is in the same initial state; Using a detector to perform real-time detection on the state parameters of the storage unit, the state parameters including the resistance value, capacitance value and temperature value of the storage unit; Performing charge trap repair on the insulating layer of the memory cell, scanning the insulating layer with a laser beam to eliminate trapped charges, so as to improve tunneling efficiency; During the charge trap repair process, a feedback control algorithm is used to adjust the laser parameters according to the laser beam scanning results. The expression of the feedback control algorithm is: , where I laser (t) is the laser current, P target is the target power, P actual (t) is the actual power, R unit (t) is the resistance value of the memory cell, T unit (t) is the temperature value of the storage unit, and k1 and k2 are coefficients adjusted according to the material characteristics of the insulating layer.

4. The high-speed writing method for a solid-state storage device according to claim 1, wherein: The adaptive quantum tunneling algorithm comprises: Before writing, inputting the resistance value, capacitance value, temperature value and previously written data features of the storage unit through a machine learning model to evaluate the current state of the solid-state storage device and obtain an evaluation result; According to the evaluation result, dynamically adjusting the write parameters, the steps include: Calculate the characteristic vector x of the current state; Use the pre-trained neural network model f to make predictions and output the optimal write parameter y; The optimal write parameters are calculated using the following expression: , where A is the feature weight matrix, B is the bias vector, C is the correction weight matrix, and D is the correction bias vector; During the writing process, the machine learning model is updated in real time to adapt to the dynamic changes of the storage device.

5. The high-speed writing method for a solid-state storage device according to claim 1, wherein: The step of simultaneously writing into a plurality of storage cells by parallel quantum tunneling comprises: Using a multi-core control circuit to write to a plurality of said storage units simultaneously, each of said storage units being independently controlled to synchronize and independently write operations; Decomposing the write operation into multiple time slices by using time division multiplexing, and writing a group of the storage units in each time slice to improve the write efficiency; The optimal write order for each of the time slices is calculated using the following expression: , where s represents the optimal write order, is an index vector of a storage unit, represents the order of writing units in each time slice, s' represents the candidate write order, represents the possible write order, argmax s' represents the candidate write order s' that makes the f(s') value the largest, n represents the total number of storage units, i represents the i-th storage unit, d s'(i) represents the distance from the i-th storage unit to the control circuit, R s'(i) represents the resistance value of the i-th storage unit, C s'(i) represents the capacitance value of the i-th storage unit, log(1+C s'(i) ) means taking the logarithm of the capacitance value and adding 1 to avoid the situation where the denominator is 0 and to balance the influence of the capacitance value.

6. The high-speed writing method for a solid-state storage device according to claim 1, wherein: The step of using a verification algorithm to verify the data written into the solid-state storage device comprises: Data verification is performed through the electron motion state during quantum tunneling to improve verification accuracy; Use a multi-level verification algorithm to verify the low-level and high-level features of the data to ensure data integrity; The verification algorithm comprises the following steps: Calculate the low-level feature vector F1 of the data; Calculate the high-level eigenvector F2 of the data; Use the following expression for comprehensive verification: , where A is the low-level feature weight matrix, B is the high-level feature weight matrix, C is the temperature weight matrix, and T is the temperature vector.

7. The high-speed writing method for a solid-state storage device according to claim 1, characterized in that: The writing method further comprises the following steps: During the writing process, cryogenic cooling is used to maintain the temperature range of the memory cell to increase the writing speed of quantum tunneling; The low temperature cooling includes active cooling and passive cooling, the active cooling is controlled by a micro cooling system, and the passive cooling is achieved by heat dissipation materials and structural design; The active cooling system calculates the optimal cooling power using the following expression: , where P cool is the cooling power, T current is the current temperature, T target is the target temperature, V write is the write voltage, I write is the write current, and k3 is the adjustment coefficient.

8. The high-speed writing method for a solid-state storage device as claimed in claim 1, characterized in that: The writing method further comprises the following steps: Before writing, the storage unit of the storage device is wear-leveled to ensure that the wear degree of each unit is uniform; The wear leveling processing step comprises: Calculate the wear level W of each storage unit i , and list the wear degree matrix W; Use wear leveling algorithm to redistribute written data to ensure even wear; The expression of the wear leveling algorithm is: , where D new is the redistributed data matrix, D old is the original data matrix, W is the wear degree matrix, and A and B are adjustment matrices.

9. The high-speed writing method for a solid-state storage device as claimed in claim 1, characterized in that: The writing method further comprises the following steps: Adopt a multi-layer data verification mechanism to improve the reliability of writing by verifying data in many aspects; The multi-layer data verification mechanism includes physical layer verification, logical layer verification and application layer verification, and the verification algorithm of each layer runs independently and verifies each other; The physical layer checksum uses the following expression to calculate the checksum value: , where C phy is the physical layer check value, V i is the voltage vector of the i-th storage unit, I i is the current vector of the i-th storage unit, T i is the temperature vector of the i-th storage unit, N is the total number of storage units; The logic layer checksum uses the following expression to calculate the checksum value: , where C log is the logic layer checksum, D i is the data vector of the i-th logic block, W i is the weight vector of the i-th logic block, R log,i is the error rate of the ith logic block, M is the total number of logic blocks; The application layer checksum uses the following expression to calculate the checksum value: , where C app is the application layer checksum value, H j is the data hash vector of the jth application layer, S j is the check code vector of the jth application layer, Q app,j is the checksum strength of the jth application layer, and K is the total number of application layer data blocks.

10. A high-speed writing system for a solid-state storage device, characterized in that: The writing system comprises: A voltage generation module, implemented by a high-precision voltage controller, is used to generate pulse voltage under quantum tunneling conditions; A pre-processing module, including charge balancing, state detection and insulation layer repair, is used to pre-process the storage unit; An adaptive quantum tunneling algorithm module that dynamically adjusts write parameters based on the current state of the storage device and environmental conditions; A parallel writing module, which writes to multiple storage cells simultaneously through a multi-core control circuit to achieve parallel quantum tunneling; A real-time monitoring module uses sensors to detect the electron motion state and physical characteristics of the storage unit during the writing process to provide real-time feedback; The data verification module uses self-verification based on quantum tunneling to ensure data integrity and accuracy; A cryogenic cooling module that uses active and passive cooling techniques to keep the temperature of the storage unit within an optimal range to improve the stability of quantum tunneling; A wear leveling module performs wear leveling on storage units to extend the life of storage devices; The multi-layer data verification mechanism module is used to improve the reliability of data writing through multi-layer verification at the physical layer, logical layer and application layer; Communication interface module, supporting multiple data transmission protocols, used to achieve communication with external devices; The power management module provides power supply and energy optimization for the writing system.

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