Soft error rate evaluation method, soft error rate evaluation program, and soft error rate evaluation device

Abstract

The present invention reduces an environmental load by shortening an acceleration test time of a device, reducing an irradiation test cost, and reducing energy consumption of a radiation generator such as a particle accelerator. Provided is a soft error rate evaluation method including: a radiation irradiation step of irradiating an electronic device executing a test program with radiation; a soft error detection step of detecting a soft error that has occurred in the electronic device; a soft error rate calculation step of calculating a soft error rate on the basis of the result of detecting the soft error; a soft error rate change calculation step of calculating the amount of change in the soft error rate; and an execution time ratio adjustment step of extracting a test program having a small error frequency from a plurality of test programs after executing the steps from the soft error detection step to the soft error rate change calculation step for each of the plurality of test programs, and making an adjustment such that the execution time ratio of the test program having a small error frequency becomes larger.

Description

Soft error rate evaluation method, soft error rate evaluation program, and soft error rate evaluation device

[0001] The present invention relates to a soft error rate evaluation method, a soft error rate evaluation program, and a soft error rate evaluation device for evaluating the soft error rate of electronic devices caused by radiation exposure.

[0002] A soft error analysis device disclosed in Patent Document 1 is known as a device for analyzing soft errors that occur in a computer. For example, the abstract of this document describes a soft error analysis device that generates a soft error in a simulator of a target microcomputer and analyzes the impact of the soft error on the target microcomputer, the soft error analysis device including: error information storage means in which at least one of the error content and the location of the error is registered for each functional block included in a program executed by the target microcomputer; functional block identification means that identifies the functional block currently being executed based on address information of an instruction executed by the simulator; error setting means that reads the error content or the location of the error for the functional block identified by the functional block identification means from the error information storage means and sets a soft error in the simulator based on at least one of the error content or the location of the error; and evaluation means that evaluates the impact of the soft error by comparing a value that the simulator stores in a predetermined variable after the soft error is set with a normal value that would have been stored in the predetermined variable when the soft error was not set.

[0003] JP 2014-160421 A

[0004] With the recent advancement of digital society, electronic and electrical equipment are being placed in various locations and are connected by networks. These electronic and electrical equipment are equipped with semiconductor devices, which control the main functions of the equipment. However, as semiconductor devices become smaller and more highly integrated, the problem of environmental radiation soft errors is becoming more prevalent, and the scope of the impact is also expanding as the number of electronic and electrical equipment increases. Furthermore, when these devices are connected and operated by a network, an event that occurs in one location propagates via the network, affecting the entire system.

[0005] Environmental radiation soft errors are a phenomenon in which data stored in logic or memory is inverted due to naturally occurring radiation such as alpha rays or neutron rays.Soft errors are transient malfunctions and are distinguished from hard errors, which cause permanent hardware failure.

[0006] Conventionally, soft errors have mainly been single-bit inversions in memory devices. However, with the recent trend toward miniaturization and high integration of semiconductor devices, phenomena such as multiple-bit inversions at once and data inversions in logic circuits such as flip-flops have become more apparent.

[0007] Furthermore, there are concerns about an increase in intermittent system failures caused by the above-mentioned environmental radiation soft errors in electronic and electrically powered equipment operating in mission-critical systems, such as autonomous driving systems. Therefore, the soft error tolerance of electronic and electrically powered equipment, i.e., the soft error rate, is an important indicator of system reliability.

[0008] There are two typical methods for evaluating soft error rates: field testing and accelerated testing. Field testing is a method in which multiple devices and types of devices are operated for long periods of time in a typical installation environment to evaluate the actual soft error rate. Accelerated testing, on the other hand, is a method in which the device is forcibly exposed to a large amount of artificially generated radiation using a particle accelerator to evaluate the soft error rate in a short period of time.

[0009] Field testing utilizes naturally occurring environmental radiation, making it possible to determine the true soft error rate of the target device. However, collecting a sufficient amount of data (number of errors) for reliability requires a large number of evaluation samples and testing times measured in years.

[0010] On the other hand, in accelerated testing, the characteristics of the environmental radiation (such as energy distribution) cannot be perfectly reproduced, so the true soft error rate cannot be obtained, but a rough estimate of the soft error rate can be made even with a test that lasts for a few hours.

[0011] Long-term field tests are currently being conducted for memory devices, for which large quantities of samples can be prepared inexpensively, but it is difficult to conduct field tests for all products.In particular, for evaluating the soft error resistance of low-volume production devices or expensive devices, accelerated testing is commonly used, in which a large amount of radiation is generated in a particle accelerator and the electronic or electrical equipment being evaluated is irradiated with that radiation.

[0012] Particle accelerators increase particle speed by 10 ６ From 10 ９ When using a particle accelerator with such specifications, and taking into account the order of magnitude of the soft error rate of a single semiconductor device today, the accelerated testing time required to collect the number of error events required for analysis will be approximately 24 hours to several days.

[0013] While standard testing methods (procedures, soft error rate calculation methods, etc.) for accelerated soft error testing using radiation exposure are specified for memory devices, specific testing methods have not been specified for logic devices such as ASICs and processors. Furthermore, in the case of logic devices, the incidence of malfunctions due to soft errors varies depending on the circuit configuration, operating mode, and operating program, so testing is required for each operation, which requires more testing time. In particular, when the incidence of malfunctions due to soft errors is relatively low depending on the operating state, it takes time to accumulate the number of error events required to calculate the incidence of malfunctions due to soft errors in that operating state (hereinafter referred to as the functional error rate), which lengthens the testing time for the entire logic device.

[0014] When testing an entire electronic or electric device, there are many semiconductor devices installed, and their radiation tolerance levels vary. In order to accumulate the required number of error events, it is necessary to match them to semiconductor devices with low error rates. This increases the test time, and increases the test costs and power consumption of the particle accelerator during testing. Therefore, with the increasing need for soft error evaluation of electronic and electric devices, establishing a test method for logic devices and reducing the test time are challenges.

[0015] The technology described in Patent Document 1 is a soft error analysis device that generates a soft error in a simulator of a microcontroller to be evaluated and analyzes the impact on the microcontroller. The system (analysis device) includes a means for injecting a soft error into the microcontroller's operation simulator and a means for reading the results, and evaluates the error propagation state when a soft error occurs on the microcontroller. Thus, Patent Document 1 focuses on the fact that the impact of soft errors varies depending on the microcontroller's function, but is limited to analyzing soft error propagation using a simulator and does not include a configuration for actually detecting soft errors by irradiating the microcontroller with radiation or outputting information on the actual operating state (functions that are operating). Furthermore, while Patent Document 1 targets microcontrollers, it assumes that the location where a soft error occurs is a memory block within the microcontroller, and only considers evaluating the memory.

[0016] The present invention has been made in consideration of the above points, and aims to reduce the environmental load by shortening the test time and reducing the cost of irradiation testing, and by reducing the energy consumption of radiation generators such as particle accelerators, when irradiating an evaluation target (a logic device alone or an apparatus or system equipped with multiple devices) equipped with a program, logic circuit, etc., with radiation generated by a particle accelerator or the like to evaluate soft errors that occur due to nuclear spallation reactions in semiconductor devices and functional errors caused by soft errors.

[0017] In order to solve the above-mentioned problems, one aspect of the present invention is a soft error rate evaluation method for evaluating the soft error rate of an electronic device irradiated with radiation, the soft error rate evaluation method comprising: a radiation irradiation step of irradiating radiation to an electronic device that is executing a test program that defines a combination of operations or functions to be used; a soft error detection step of detecting soft errors that occur in the electronic device during radiation irradiation; a soft error rate calculation step of calculating a soft error rate based on the soft error detection results; a soft error rate change calculation step of calculating a change in the soft error rate; an execution time ratio adjustment step of extracting test programs with a low error frequency from the plurality of test programs and adjusting the execution time ratio of the test programs with a low error frequency so that it is larger; and a control step of controlling the electronic device to execute each of the plurality of test programs at the adjusted execution time ratio.

[0018] According to the present invention, the efficiency (shortening of irradiation time) and accuracy of radiation soft error evaluation are improved, and further, the test time is shortened, thereby reducing the cost of irradiation testing and the environmental load by reducing the energy consumption of radiation generators such as accelerators.

[0019] 1 is a diagram showing an example of the configuration of a soft error rate evaluation system according to a first embodiment; FIG. 2 is a processing flowchart of the soft error rate evaluation system according to the first embodiment; FIG. 3 is an example of the hardware configuration of a soft error rate evaluation device according to the first embodiment; FIG. 4 is an example of a soft error database; FIG. 5 is an example of a functional error database; FIG. 6 is an example of an SDC database; FIG. 7 is an example of a time series table of error rates; FIG. 8 is a diagram showing the convergence process of error rates according to the first embodiment; FIG. 9 is a diagram showing an example of a functional error detection mechanism according to the first embodiment; FIG. 10 is a diagram showing an example of a functional error detection mechanism equipped with storage of a functional error detection signal; FIG. 11 is a diagram showing an example of the configuration of a soft error rate evaluation system according to a second embodiment;

[0020] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that, for convenience, the following embodiments will be divided into multiple embodiments for description, unless otherwise specified. However, unless otherwise specified, these embodiments are not unrelated to one another, and one is related to the other by partial or complete modifications, details, supplementary explanations, etc. Furthermore, in the following embodiments, when the number of elements (including numbers, numerical values, amounts, ranges, etc.) is mentioned, it is not limited to the specific number, and may be more or less than the specific number, unless otherwise specified or clearly limited to a specific number in principle. Furthermore, in the following embodiments, it goes without saying that the components (including element steps, etc.) are not necessarily essential, unless otherwise specified or clearly considered essential in principle.

[0021] Similarly, in the following examples, when referring to the shapes, positional relationships, etc. of components, etc., it is intended to include those that are substantially similar or approximate to those shapes, etc., unless otherwise specified or when it is considered that this is clearly not the case in principle. The same applies to the above-mentioned numerical values ​​and ranges. Furthermore, in all drawings used to explain the examples, the same components are generally designated by the same reference numerals, and repeated explanations thereof will be omitted. Hereinafter, each example of the present invention will be described with reference to the drawings.

[0022] 1 shows an example of the configuration of a soft error rate evaluation system according to a first embodiment of the present invention. As shown in the figure, the system includes a radiation irradiation facility 1, an evaluation object 2, and a soft error rate evaluation device 3. Each of these will be described in turn below.

[0023] <Radiation irradiation equipment 1> The radiation irradiation equipment 1 includes a particle accelerator 11 that accelerates charged particles such as protons, an accelerator control device 12 that controls the particle accelerator 11, and a target metal 13 that is irradiated with the accelerated charged particles to generate a neutron beam. Note that the target metal 13 may be omitted, and the charged particles may be directly irradiated.

[0024] <Evaluation Object 2> Evaluation Object 2 is an electronic device for which evaluation tests are performed to determine the soft error rate and functional error rate when irradiated with neutron rays (or charged particles), and specifically, is an apparatus or system equipped with a logic device or multiple devices equipped with programs, logic circuits, etc. This evaluation object 2 has the function of detecting soft errors and functional errors, and has an interface for outputting soft error detection signals and functional error detection signals to the outside.

[0025] <Soft Error Rate Evaluation Device 3> The soft error rate evaluation device 3 includes a soft error signal input unit 31, a soft error rate calculation unit 32, a functional error signal input unit 33, an execution state information input unit 34, a functional error rate calculation unit 35, an error correlation calculation unit 36, an execution order adjustment unit 37, an optimization rule memory 37 a, an evaluation target control unit 38, a soft error database DB1, and a functional error database DB2.

[0026] Each of these is a functional unit realized by executing a corresponding program, or a database that stores specified data. The hardware configuration required to realize each will be described later using Figure 3, but the functions of each can be summarized as follows.

[0027] That is, the soft error signal input unit 31 temporarily stores the soft error detection signal from the evaluation object 2. The soft error rate calculation unit 32 calculates the soft error rate based on the soft error detection signal. The soft error database DB1 stores the calculation results of the soft error rate.

[0028] Furthermore, the functional error signal input unit 33 temporarily stores functional error detection signals from the evaluation object 2. The execution state information input unit 34 temporarily stores execution state information such as the operating state (operation settings) of the evaluation object 2 and programs currently being executed. The functional error rate calculation unit 35 calculates the functional error rate based on the soft error detection signal, the functional error detection signal, and the execution state information. The functional error database DB2 stores the calculation results of the functional error rate.

[0029] Furthermore, the error correlation calculation unit 36 ​​compares the magnitude of the error rates for each operational setting and program during the accelerated test based on the execution state information, soft error rate, and functional error rate. The execution order adjustment unit 37 refers to the optimization rules stored in the optimization rule memory 37a and adjusts the operational setting, program execution order, and execution time ratio for the evaluation target 2. The evaluation target control unit 38 converts the execution order and execution time ratio adjusted by the execution order adjustment unit 37 into control instructions for the evaluation target 2 and outputs them.

[0030] <Soft Error Rate Evaluation Procedure> Next, the control of each procedure and the data flow in the soft error rate evaluation system of this embodiment will be described with reference to the flowchart of FIG.

[0031] First, in step S1, the radiation irradiation equipment 1, the evaluation object 2, and the soft error rate evaluation device 3 are started up to start the evaluation of the soft error rate.

[0032] Next, in step S2, the evaluation object 2 is initialized and the program, logic circuit, etc. are started to operate.

[0033] In step S3, the radiation irradiation equipment 1 starts irradiating the evaluation object 2 with a radiation beam (neutron beam or charged particle beam).

[0034] In step S4, the radiation irradiation equipment 1, the evaluation object 2, and the soft error rate evaluation device 3 each perform a prescribed radiation irradiation evaluation flow. As shown in the figure, the prescribed radiation irradiation evaluation flow includes an error detection process in the evaluation object 2, an error information process in the soft error rate evaluation device 3, a reset / restart process for each device, and a radiation beam stop process in the radiation irradiation equipment 1.

[0035] In step S5, it is determined whether the scheduled irradiation time (e.g., 24 hours) has ended. If the requirements are met, the process proceeds to step S6 and the evaluation is terminated. On the other hand, if the requirements are not met, the process returns to step S3 and the evaluation continues.

[0036] <<If a soft error is detected>> If, during the execution of step S4, the evaluation object 2 detects malfunction (error) information caused by a soft error that occurs due to a spallation reaction within the semiconductor device, the following steps S7 to S10 are executed.

[0037] First, in step S6, the soft error signal input unit 31 of the soft error rate evaluation device 3 acquires a soft error detection signal from the evaluation target 2. This soft error detection signal is a pulse signal output when a soft error occurs, or data (e.g., an error code) indicating the occurrence of a soft error. If the signal is a pulse signal, the soft error signal input unit 31 detects a change point in the signal, and if the signal is data, it performs a decoding process and notifies the soft error rate calculation unit 32 of the occurrence of a soft error. The soft error rate calculation unit 32 then calculates the soft error rate based on the soft error detection signal. The method for calculating the soft error rate will be described later.

[0038] In step S7, the soft error rate calculation unit 32 stores the calculated soft error rate in the soft error database DB1.

[0039] In step S8, the soft error rate calculation unit 32 calculates the amount of change in the soft error rate based on the time-series change in the soft error rate stored in the soft error database DB1.

[0040] In step S9, the error correlation calculation unit 36 ​​rearranges the error rates calculated in step S8 by operation setting or program based on the time-dependent change in the error rate, and outputs the error correlation calculation results to the execution order adjustment unit 37.

[0041] <<If a Functional Error is Detected>> If, during the execution of step S4, the evaluation object 2 detects malfunction (error) information caused by a functional error that occurs due to a nuclear spallation reaction within the semiconductor device, the following steps S11 to S14 are executed.

[0042] First, in step S11, the functional error signal input unit 33 of the soft error rate evaluation device 3 acquires a functional error detection signal from the evaluation target 2. This functional error detection signal is a pulse signal that is output when a functional error occurs, or data indicating the occurrence of a functional error (e.g., an error code, etc.). Then, the functional error signal input unit 33 notifies the functional error rate calculation unit 35 of the occurrence of the functional error.

[0043] At the same time, the execution state information input unit 34 transmits the execution state information of the evaluation target 2 to the functional error rate calculation unit 35. The execution state information is information that indicates the operation state and location when an error occurs, such as the operation settings and the name of the execution program when an error is detected in the evaluation target 2, for example.

[0044] The soft error signal input unit 31 also notifies the functional error rate calculation unit 35 of the occurrence of a soft error. Radiation-induced errors can be classified into three types: soft errors that directly detect the inversion of a data bit in a semiconductor device due to radiation; functional errors that result in unexpected functional operation due to a soft error (i.e., data bit inversion); and silent data corruption (SDC) that results in unexpected functional operation even though the soft error is not detected (i.e., data bit inversion could not be detected). Therefore, depending on the order change rules in the execution order adjustment unit 37, soft errors, functional errors, and SDC may be taken into consideration.

[0045] Then, the functional error rate calculation unit 35 calculates the functional error rate based on the outputs of the soft error signal input unit 31, the functional error signal input unit 33, and the execution state information input unit 34. The method for calculating the functional error rate will be described later.

[0046] In step S12, the function error rate calculation unit 35 stores the calculated function error rate in the function error database DB2.

[0047] In step S13, the function error rate calculation unit 35 calculates the amount of change in the error rate of the function error based on the time-series change in the function error rate stored in the function error database DB2.

[0048] In step S14, the error correlation calculation unit 36 ​​rearranges the error rates calculated in step S13 by operation setting or program based on the time-dependent change in the error rate, and outputs the error correlation calculation results to the execution order adjustment unit 37.

[0049] In steps S9 and S14, the sorted results may be held in the error correlation calculation unit 36 ​​and then output, or the sorted results may be held in the soft error database DB1 and the functional error database DB2. When sorting is performed in each database and the results are held, operation instructions to each database are generated and output from the error correlation calculation unit 36.

[0050] <<Processing After Error Correlation Calculation>> After calculating the error correlation using the above procedure, in step S15, the execution order adjustment unit 37 selects the operation settings and programs to be executed while the evaluation object 2 is being irradiated with radiation, in accordance with the contents of the optimization rule memory 37a, and sends the results to the evaluation object control unit 38. For example, the order can be changed to prioritize execution of functions with a low frequency of functional errors, and the cumulative neutron dose over irradiation time can be increased, thereby obtaining the number of errors (number of error events) required for evaluation. If the number of error events is small, the accuracy of the soft error rate will be low, and the reliability of the evaluation will be reduced.

[0051] Finally, in step S16, the evaluation target control unit 38 generates and outputs operation settings based on the interface specifications with the evaluation target 2 and instructions for switching the execution program.

[0052] 3, an example of the hardware configuration of the soft error rate evaluation device 3 will be described. As shown in the figure, the soft error rate evaluation device 3 of this embodiment is composed of a computer 100 in which a processor 101, a main memory device 102, an auxiliary memory device 103, a communication device 104, an output device 105, and an input device 106 are connected via a data bus.

[0053] The processor 101 includes a CPU, a GPU, an FPGA, etc., and controls the entire computer 100. The main memory device 102 is a volatile memory device such as a random access memory (RAM). The auxiliary memory device 103 is a non-volatile memory device capable of storing digital information, such as a hard disk drive (HDD), a solid state drive (SSD), or a flash memory.

[0054] The input device 106 includes a keyboard, a mouse, a touch panel, a control bus, a data bus, etc. The output device 105 includes a display, a printer, a control bus, a data bus, etc.

[0055] The communication device 104 is composed of a NIC (Network Interface Card) or the like. The communication device 104 communicates with other devices connected to the same network by at least one of wired communication and wireless communication. For this communication, packet communication using TCP / IP (Transmission Control Protocol / Internet Protocol) is adopted, but this is not limited thereto, and communication using other protocols such as UDP (User Datagram Protocol) may also be adopted.

[0056] The hardware configuration of the computer 100 is not limited to the above example, and some of the above components may be omitted or other components may be included. The computer 100 may also be any of various information processing devices, such as a server computer, a personal computer, a notebook computer, a tablet computer, a smartphone, or a television device.

[0057] The computer 100 can store and externally load programs such as an operating system, middleware, and application programs, and can perform various processes by having the processor 101 execute these programs.

[0058] The soft error signal input unit 31, functional error signal input unit 33, and execution state information input unit 34 of the soft error rate evaluation device 3 are executed by the input device 106 and processor 101 of the computer 100. The soft error rate calculation unit 32 and functional error rate calculation unit 35 store procedures in the main memory device 102 and are executed by the processor 101 in accordance with the procedures. The soft error database DB1 and functional error database DB2 execute procedures by the processor 101 and main memory device 102 and store data in the main memory device 102 and auxiliary memory device 103. Furthermore, the error correlation calculation unit 36, evaluation order adjustment unit 37, and evaluation target control unit 38 execute procedures by the processor 101 and main memory device 102, and the evaluation target control unit 38 outputs the selection result of the execution function to the evaluation target 2 by the output device 105. The procedures executed by the input device 106 and output device 105 may be executed by the communication device 104.

[0059] <Data Configuration Example> Figures 4A to 4D show configuration examples of collected data and error rate calculation progress data. Details of each figure will be explained in order below.

[0060] <<Soft Error Database DB1>> Fig. 4A is an example of the configuration of the soft error database DB1. In this example, the name of the program executed on the evaluation target 2 is used as a key field, and the execution time (e.g., data in seconds) and execution time ratio (= program execution time / total execution time of all programs) of that program are stored. The execution time and execution time ratio are information that is stored in advance before the start of testing.

[0061] After the accelerated test starts, the soft error rate calculation unit 32 stores the number of soft errors since the start of the test, and accumulates the number of soft errors when a soft error detection signal is input, and stores the result in the error event number field. The soft error rate calculation unit 32 also calculates the average soft error rate from the number of error events. An example of a formula for calculating the average soft error rate is shown in Equation 1.

[0062]

[0063] (S: average soft error rate [FIT], E ｎ[MeV]: incident neutron energy, E ｔｈ [MeV]: threshold energy of the device (energy value that causes an error), Φ ｖ (En): Flux [ / cm ２ / s]) σ ＳＥＵ (E ｎ ) = n / Φ(E ｎ ) and each parameter is: n: number of error events, Φ(E ｎ ): Fluence.

[0064] The number of error events n is the number of error events in the configuration example of the soft error database DB1, and the other parameters are determined in advance from the specifications of the particle accelerator 11 and the evaluation object 2, and are stored in the soft error rate calculation unit 32 before the start of the test.

[0065] <<Function Error Database DB2>> Figure 4B shows an example of the configuration of the function error database DB2. In this example, like the soft error database DB1, the execution time and execution time ratio are stored in advance. Similarly, when function error information from evaluation target 2 is input, the number of error events is cumulatively added to the number of errors since the start of the test and stored. The average function error rate field is calculated using the following formula 2.

[0066]

[0067] (F: Functional Error Rate [FIT], t ｍ : Total neutron irradiation time [h], A ｍ : acceleration rate relative to the amount of neutrons on the ground, n ｆ : number of functional error events) Equation 2 is an example in which the radiation to be irradiated is a neutron beam, and the total neutron irradiation time from the start of the test is set based on information from the particle accelerator 11. ｍ is calculated from the particle accelerator 11 of the evaluation object 2 or the irradiation dose value of the particle accelerator 11 corrected for the distance from the target 4, and set in advance. ｆ is the number of error events in the configuration example of the function error database DB2.

[0068] <<SDC Database DB3>> Figure 4C shows an example of the configuration of the SDC database DB3, which is a variant of the functional error database DB2. If a soft error detection signal is not received during a functional error occurrence event, this indicates that the soft error detection mechanism in the evaluation target 2 was unable to detect the error, and only a functional failure occurred (SDC). This SDC rate may also be tested, and the number of error events and the values ​​of each field are saved in the configuration of the SDC database DB3, just like the functional error database DB2.

[0069] <<Error Rate Time Series Table DB4>> Figure 4D shows an example of the configuration of time series table DB4, which records the changes in error rates over time in the soft error database DB1 and functional error database DB2 (or SDC database DB3) described above. While the average error rates in each of the above databases store the most recent values, time series table DB4 stores the results of calculating the average error rate over time. This time series table DB4 is provided for each soft error and functional error. The error correlation calculation unit 36 ​​searches this time series table DB4 and calculates the degree of convergence of the error rate.

[0070] 5 shows the program of the present invention and the convergence process of error rate calculation. This shows an example in which programs P1, P2, and P3 are executed in order as a test program P that defines the operation when an accelerated test is performed by irradiating radiation on an evaluation target 2. Note that program P1 is, for example, a program that uses functions Fa, Fb, and Fd; program P2 is, for example, a program that uses functions Fb, Fc, and Fe; and program P3 is, for example, a program that uses functions Fc and Fe.

[0071] 5(a) and 5(b) are graphs showing the soft error rate on the vertical axis and the radiation exposure time on the horizontal axis. The radiation irradiated by the radiation irradiation equipment 1 induces random errors in the evaluation object 2. Since the error occurrence interval follows a Poisson distribution, the soft error rate during execution of each program should converge to an error rate according to the circuit scale, integration level, etc. of the logic device used in that program. Therefore, when evaluating the soft error rate through accelerated testing, it is necessary to continue the accelerated testing until a sufficient amount of time has passed for the soft error rate to converge to a certain value by accumulating error events.

[0072] 5A shows the convergence of the soft error rate when accelerated testing of programs P1, P2, and P3 is performed at equal time intervals. In this example, the soft error rates of programs P2 and P3 converge relatively quickly, while program P1 takes the longest time to converge. In other words, FIG. 5A shows that the error occurrence intervals of the logic devices used by programs P2 and P3 are relatively short, while the error occurrence intervals of the logic device used by program P1 are relatively long. Therefore, in this example, the accelerated testing must be continued until the error rate of program P1 converges.

[0073] On the other hand, Figure 5(b) shows the effect of adjusting the program execution order and execution time ratio according to this embodiment. In this example, the execution time ratio of program P1, which was found to have the longest error interval in the test of Figure 5(a) , is increased (+30% in the example of Figure 5(c) ). Similarly, the execution time ratio of program P2, which was found to have a longer error interval than program P3 in the test of Figure 5(a) , is also increased somewhat (+10% in the example of Figure 5(c) ). In this way, by setting the execution time ratio of each program so that it is approximately inversely proportional to the error interval of each program, the time required to accumulate error events for programs P1 and P2 is shortened and equalized with the time required to accumulate error events for program P3, thereby shortening the time required to complete the accelerated test compared to the example of Figure 5(a) . Note that Figure 5 describes a method for shortening the time required for accelerated testing to evaluate soft error rates. However, a similar method can be used to shorten the time required for accelerated testing to evaluate functional error rates.

[0074] <Example of Functional Error Detection Mechanism> Figure 6 shows an example of a functional error detection mechanism 62 that detects functional errors caused by soft errors. In this example, the evaluation object 2 is a logic LSI 61, and the logic block is composed of functions Fa to Fe. In this example, a mechanism is provided that outputs a soft error detection signal to the outside of the LSI when a soft error is detected within the logic LSI 61. Many general LSIs have a built-in mechanism that detects soft errors even when in actual use, and this example also has a similar mechanism installed.

[0075] Even if a soft error occurs in the logic LSI 61, it may not affect its functionality, and the soft error rate and functional error rate are usually not the same. Therefore, when the logic LSI 61 is the test target, the presence or absence of a functional error is determined by whether or not the output signal differs from the expected value.

[0076] In this example, the functional error detection mechanism 62 compares the output of the logic LSI 61 with the expected value stored in the expected value memory 63 using a comparator 64, and if they do not match, outputs a functional error detection signal. In this example, a configuration example is shown that focuses on the basic concept of functional error detection, but synchronization between the operation sequence of the logic LSI 61 and the expected value must be considered separately.

[0077] As another method for generating expected value data, the expected value memory 63 may be implemented as a redundant circuit of the logic LSI 61 and executed simultaneously. This functional error detection process may be implemented within the evaluation object 2, or may be provided outside the evaluation object 2, or may be provided in the soft error rate evaluation device 3.

[0078] Fig. 7 shows an example of a functional error detection mechanism 62a having a function of storing the detection results of functional errors, which is a modification of the functional error detection mechanism 62 in Fig. 6. This functional error detection mechanism 62a outputs functional errors to the soft error rate evaluation device 3 in the same way as in Fig. 6, and also acquires functional error information by a comparison result acquisition processing procedure 65 and stores the results in a comparison result storage database 66.

[0079] With this configuration, when a functional malfunction occurs during normal operation of the evaluation object 2, the comparison result information stored in the comparison result storage database 66 can be used to compare with the pattern of functional errors occurring in the evaluation object 2. This can be used to determine whether the functional error is caused by a soft error or by other factors such as hardware failure. Also, immediately after the functional error occurs, the program executed during the irradiation test can be run to observe the pattern of functional error occurrence and compare it with the stored data.

[0080] As a result, it is possible to determine whether an event in which the state disappears due to power off or system reset is caused by a soft error during operation.

[0081] 6 , it may be incorporated into the evaluation object 2, or may be provided outside the evaluation object 2, or may be provided in the soft error rate evaluation device 3. Furthermore, only the comparison result acquisition processing procedure 65 and the comparison result storage database 66 may be provided outside the evaluation object 2 or in the soft error rate evaluation device 3.

[0082] <Effects of this Example> The present example described above improves the efficiency (shortening of irradiation time) and accuracy of radiation soft error evaluation, and also shortens the test time, thereby reducing the cost of irradiation testing and the environmental load by reducing the energy consumption of radiation generators such as accelerators.

[0083] 8 shows an example of the configuration of a soft error rate evaluation system according to Example 2 of the present invention. The soft error rate evaluation system of this example is mostly the same as that of Example 1, but in this example, a beam intensity change instruction unit 39 is added to the soft error rate evaluation device 3, and beam intensity change instruction data can be transmitted from the beam intensity change instruction unit 39 to the accelerator control device 12 of the radiation irradiation facility 1.

[0084] In this embodiment, if the number of error events stored in the soft error database DB1 according to the procedure of Example 1 is less than a predetermined threshold, or if the time series table of Figure 4D is searched and it is recognized that the soft error rate is converging too quickly, the amount of charged particles radiated by the particle accelerator 11 is increased to shorten the error occurrence interval. This makes it possible to reduce the accelerated test time required for evaluating the soft error rate. Note that if the number of error events stored in the soft error database DB1 according to the procedure of Example 1 is too large, or if the time series table of Figure 4D is searched and it is recognized that the soft error rate is converging too quickly, it is possible that the errors have not been evaluated appropriately, and therefore the amount of charged particles radiated by the particle accelerator 11 may be reduced to lengthen the error occurrence interval.

[0085] The soft error rate evaluation method described above improves the efficiency (shortening of irradiation time) and accuracy of radiation soft error evaluation, and further shortens the test time, thereby reducing the cost of irradiation testing and the environmental load by reducing the energy consumption of radiation generation equipment such as accelerators.

[0086] The present invention is not limited to the above-described examples, and various modifications are possible. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with or add to the configuration of another embodiment.

[0087] Furthermore, the components, functions, processing units, processing means, etc. of the soft error rate evaluation device 3 may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The components, functions, etc. may also be implemented in software by a processor interpreting and executing programs that implement the respective functions. Information such as programs, tables, and files that implement the respective functions may be stored in memory, a recording device such as a hard disk or SSD, or a recording medium such as an IC card, SD card, or DVD. Furthermore, the control lines and information lines shown are those considered necessary for explanation, and not all control lines and information lines are necessarily shown in the actual product. In reality, it can be assumed that almost all components are interconnected.

[0088] REFERENCE SIGNS LIST 1 Radiation irradiation equipment, 11 Particle accelerator, 12 Accelerator control device, 13 Target metal, 2 Evaluation object, 3 Soft error rate evaluation device, 31 Soft error signal input unit, 32 Soft error rate calculation unit, 33 Functional error signal input unit, 34 Execution state information input unit 35 Functional error rate calculation unit, 36 Error correlation calculation unit, 37 Execution order adjustment unit, 37a Optimization rule memory, 38 Evaluation object control unit, 39 Beam amount change instruction unit, DB1 Soft error database, DB2 Functional error database, 100 Computer, 101 Processor, 102 Main memory device, 103 Auxiliary memory device, 104 Communication device, 105 Output device, 106 Input device

Claims

1. A soft error rate evaluation method for evaluating the soft error rate of an electronic device irradiated with radiation, comprising: a radiation irradiation step of irradiating radiation to an electronic device executing a test program that defines an operation to be used or a combination of functions to be used; a soft error detection step of detecting soft errors occurring in the electronic device during radiation irradiation; a soft error rate calculation step of calculating a soft error rate based on results of the soft error detection; a soft error rate change calculation step of calculating a change in the soft error rate; an execution time ratio adjustment step of extracting a test program with a low error frequency from the plurality of test programs and adjusting the execution time ratio of the test program with the low error frequency so as to be larger; and a control step of controlling the electronic device to execute each of the plurality of test programs at the adjusted execution time ratio.

2. A soft error rate evaluation method as claimed in claim 1, further comprising: a functional error detection step of detecting a functional error occurring in said electronic device; a functional error rate calculation step of calculating a functional error rate based on the results of the functional error detection; and a functional error rate change calculation step of calculating a change in said functional error rate, wherein in said execution time ratio adjustment step, after executing the functional error detection step through the functional error rate change calculation step for each of a plurality of test programs, a test program with a low error frequency is extracted from said plurality of test programs and an adjustment is made so that the execution time ratio of the test program with the low error frequency is increased.

3. A soft error rate evaluation method as claimed in claim 2, characterized in that in the functional error detection step, the functional error is detected when an output value of the electronic device does not match an expected value of the output of the electronic device.

4. The soft error rate evaluation method according to claim 1, further comprising a radiation dose instruction generating step of generating an instruction to increase the amount of radiation irradiated in the radiation irradiation step when the error frequency during execution of the test program is lower than a predetermined threshold value.

5. A program for causing a computer to execute the steps from the soft error detection step to the soft error rate change calculation step, the execution time ratio adjustment step, and the control step as claimed in claim 1.

6. A program for causing a computer to execute the steps from the functional error detection step to the functional error rate change amount calculation step, the execution time ratio adjustment step, and the control step as recited in claim 2.

7. A soft error rate evaluation device for evaluating the soft error rate of electronic equipment irradiated with radiation by radiation irradiation equipment, comprising: a soft error detection unit for detecting soft errors occurring in an electronic equipment when radiation is irradiated to the electronic equipment while the electronic equipment is executing a test program that defines a combination of operations or functions to be used; a soft error rate calculation unit for calculating a soft error rate based on a result of the soft error detection; a soft error rate change calculation unit for calculating a change in the soft error rate; an execution time ratio adjustment unit for extracting a test program having a low error frequency from the plurality of test programs after performing the soft error detection-to-soft error change calculation for each of a plurality of test programs and adjusting the execution time ratio of the test program having a low error frequency so as to be larger; and a control unit for controlling the electronic equipment to execute each of the plurality of test programs at the adjusted execution time ratio.

8. A soft error rate evaluation device as claimed in claim 7, further comprising: a functional error detection unit which detects a functional error occurring in the electronic device when radiation is irradiated to the electronic device while the test program is being executed; a functional error rate calculation unit which calculates a functional error rate based on the results of the functional error detection; and a functional error rate change calculation unit which calculates a change in the functional error rate, wherein the execution time ratio adjustment unit performs the functional error rate change calculation from the functional error detection for each of a plurality of test programs, and then extracts a test program with a low error frequency from the plurality of test programs and adjusts the execution time ratio of the test program with the low error frequency so as to be larger.

9. A soft error rate evaluation device according to claim 8, wherein the functional error detection unit detects the functional error when an output value of the electronic device does not match an expected value of the output of the electronic device.

10. The soft error rate evaluation device according to claim 7, further comprising a radiation dose instruction generating unit which generates an instruction to increase the amount of radiation irradiated by the radiation irradiation equipment when the error frequency during execution of the test program is lower than a predetermined threshold value.

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