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

Abstract

To reduce an environmental load due to reduction in an acceleration test time of a device, the reduction in an irradiation test cost, and the reduction in consumption energy of a radiation generator such as a particle accelerator.SOLUTION: A soft error ratio evaluation method includes: a radiation irradiation step of irradiating an electronic device which is executing a testing program with radiation; a soft error detection step of detecting a soft error generated in the electronic device; a soft error ratio calculation step of calculating a soft error ratio based on a detection result of the soft error; a soft error ratio change amount calculation step of calculating a change amount of the soft error ratio; and a running time ratio adjustment step of extracting a testing program having a small error frequency from a plurality of testing programs, after executing the steps from the soft error detection step to the soft error ratio change amount calculation step for each of the plurality of testing programs, and adjusting a running time ratio so that the running time ratio of the testing program having the small error frequency becomes greater.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[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 the document describes a soft error analysis device that generates a soft error in a simulator of a target microcomputer and analyzes the effect on the target microcomputer, the soft error analysis device having an error information storage means in which at least one of the error contents or the error occurrence location of a soft error is registered for each functional block included in a program executed by the target microcomputer, a functional block identification means that identifies a functional block being executed based on address information of an instruction executed by the simulator, an error setting means that reads out the error contents or the error occurrence location of 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 contents or the error occurrence location, and an evaluation means that evaluates the effect of the soft error by comparing a value that the simulator stores in a specified variable after a soft error is set with a normal value stored in the specified variable when no soft error is set. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2014-160421 A Summary of the Invention [Problem to be solved by the invention]

[0004] With the recent advancement of digital society, electronic and electric devices are placed in various places and are connected by networks. These electronic and electric devices are equipped with semiconductor devices, which are responsible for the main functions of the devices. On the other hand, as semiconductor devices become more miniaturized and highly integrated, the problem of environmental radiation soft errors is expanding, and the range of impact is also expanding due to the increase in the number of electronic and electric devices. In addition, when these devices are connected and operated by a network, an event that occurs in one place propagates through 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 particles or neutron rays. Soft errors are temporary defects and are distinct from hard errors, which cause permanent hardware failure.

[0006] Conventionally, soft errors mainly consisted of single-bit inversions in memory devices. However, with the miniaturization and high integration of semiconductor devices in recent years, phenomena such as multiple-bit inversions at once and inversion of held data in logic circuits such as flip-flops have become evident.

[0007] There are also 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, and the soft error resistance 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 the soft error rate: field testing and accelerated testing. Field testing is a method in which multiple and types of evaluation targets are operated for long periods of time in a typical installation environment to evaluate the actual soft error occurrence rate. On the other hand, accelerated testing is a method in which the evaluation target is forcibly exposed to a large amount of radiation artificially generated using a particle accelerator to evaluate the soft error rate in a short period of time.

[0009] Field testing makes use of environmental radiation that exists in nature, making it possible to determine the true soft error rate of the evaluation target. However, in order to collect a sufficient amount of data (number of errors) for reliability, a large number of evaluation samples and testing time measured in years are required.

[0010] On the other hand, in accelerated testing, the characteristics of the environmental radiation (energy distribution, etc.) cannot be completely reproduced, so the true soft error rate cannot be obtained. However, it is possible to estimate the approximate soft error rate even with testing that lasts for a few hours.

[0011] Long-term field tests are currently being conducted for memory devices, for which a large number of samples can be prepared at low cost, 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 power device 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, the accelerated test time required to collect the number of error events required for analysis will be about 24 hours to several days, considering the current order of magnitude of the soft error rate of a single semiconductor device.

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

[0014] When testing an entire electronic or electric device, there are many semiconductor devices mounted on it, and the strength of radiation resistance varies. In order to accumulate the required number of error events, it is necessary to match the semiconductor devices with low error rates. This results in longer test times, and increases the test costs and the power consumption of the particle accelerator during testing. Therefore, with the increasing need for soft error evaluation of electronic and electric devices, the challenge is to establish a test method for logic devices and reduce the test time.

[0015] The technology described in Patent Document 1 is a soft error analysis device that generates a soft error in a simulator of a microcomputer to be evaluated and analyzes the impact on the microcomputer, and is a system (analysis device) that is provided with a means for injecting a soft error into a microcomputer operation simulator and a means for reading out the result, and evaluates the error propagation state when a soft error occurs on the microcomputer. Thus, Patent Document 1 focuses on the fact that the impact of a soft error differs for each function of the microcomputer, but is limited to the purpose of analyzing the propagation of soft errors using a simulator and does not include a configuration for actually detecting a soft error by irradiating radiation or outputting information on the actual operation state (functions that are operating). In addition, although the target is a microcomputer, the location where a soft error occurs is assumed to be a memory block in the microcomputer, and only memory evaluation is considered.

[0016] The present invention has been made in consideration of the above points, and aims to reduce the test time and irradiation test costs and the environmental load 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. [Means for solving the problem]

[0017] In order to solve the above problems, one aspect of the present invention is a soft error rate evaluation method for evaluating a 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 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 a result 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 having a low error frequency from the plurality of test programs and adjusting the execution time ratio of the test program having 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. Effect of the Invention

[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. [Brief description of the drawings]

[0019] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a soft error rate evaluation system according to a first embodiment. [Diagram 2] 3 is a process flowchart of the soft error rate evaluation system according to the first embodiment. [Diagram 3] 2 shows an example of a hardware configuration of the soft error rate evaluation device according to the first embodiment. [Figure 4A] An example of a soft error database. [Figure 4B] An example of a functional error database. [Figure 4C] An example of an SDC database. [Figure 4D] An example of a time series table of error rates. [Diagram 5] FIG. 13 is a diagram showing the convergence process of the error rate when the first embodiment is carried out. [Figure 6] FIG. 2 is a diagram showing an example of a functional error detection mechanism according to the first embodiment. [Figure 7] FIG. 1 illustrates an example of a functional error detection mechanism with storage of a functional error detection signal. [Figure 8] FIG. 13 is a diagram showing an example of the configuration of a soft error rate evaluation system according to a second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] Hereinafter, the embodiments of the present invention will be described with reference to the drawings. In the following embodiments, when necessary for convenience, they will be divided into a plurality of embodiments for description, but unless otherwise specified, they are not unrelated to each other, and one is a partial or complete modification, detail, supplementary explanation, etc. of the other. In addition, in the following embodiments, when the number of elements (including the number, numerical value, amount, range, etc.) is mentioned, it is not limited to the specific number, except when specifically specified or when it is clearly limited to a specific number in principle, and it may be more than or less than the specific number. Furthermore, in the following embodiments, it goes without saying that the components (including element steps, etc.) are not necessarily essential, except when specifically specified or when it is clearly considered to be 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 similar to those shapes, etc., unless otherwise specified or considered to be obviously different in principle. This also applies to the above numerical values ​​and ranges. In addition, in all the drawings for explaining the examples, the same members are generally given the same reference numerals, and repeated explanations are omitted. Below, each embodiment of the present invention will be explained using the drawings. EXAMPLES

[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 target 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 target 2> Evaluation target 2 is an electronic device for which evaluation tests are performed on the soft error rate and functional error rate when irradiated with neutron rays (or charged particles), and specifically, is a device or system equipped with a single logic device or multiple devices equipped with programs, logic circuits, etc. This evaluation target 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 has 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 37a, 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 of these will be described later using Figure 3, but the functions of each can be roughly described 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 a functional error detection signal from the evaluation target 2. The execution state information input unit 34 temporarily stores execution state information such as the operating state (operation settings) of the evaluation target 2 and programs currently being executed. The functional error rate calculation unit 35 calculates a 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 rate for each operation setting and program during the accelerated test based on the execution state information, the soft error rate, and the functional error rate. The execution order adjustment unit 37 refers to the optimization rules stored in the optimization rule memory 37a and adjusts the operation setting, execution order, and execution time ratio of the programs in 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 in order to start the evaluation of the soft error rate.

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

[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. Note that the prescribed radiation irradiation evaluation flow includes, as shown in the figure, 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 is continued.

[0036] <<If a soft error is detected>> During the execution of step S4, if evaluation object 2 detects malfunction (error) information caused by a soft error that occurs due to a nuclear spallation reaction in a semiconductor device, the following processes of 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 it is a pulse signal, the soft error signal input unit 31 detects a change point of the signal, and if it is data, performs a decoding process and notifies the occurrence of a soft error to the soft error rate calculation unit 32. Then, the soft error rate calculation unit 32 calculates a soft error rate based on the soft error detection signal. The method of 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 operation settings and programs based on the change over time in the error rate calculated in step S8, and outputs the calculation result of the error correlation to the execution order adjustment unit 37.

[0041] <<If a function error is detected>> During the execution of step S4, if the evaluation object 2 detects malfunction (error) information caused by a functional error that occurs due to a nuclear spallation reaction in the semiconductor device, the following processes of 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. The functional error detection signal is a pulse signal 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 transmits the occurrence of a functional error to the functional error rate calculation unit 35.

[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 position 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] In addition, the soft error signal input unit 31 transmits the occurrence of a soft error to the functional error rate calculation unit 35. Errors caused by radiation 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 an unexpected functional operation due to a soft error (i.e., an inversion of a data bit), and SDC (Silent Data Corruption) that result in an unexpected functional operation even though it is not detected as a soft error (i.e., an inversion of a data bit could not be detected). Therefore, depending on the rule for changing the order 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 section 35 calculates the functional error rate based on the outputs of the soft error signal input section 31, the functional error signal input section 33, and the execution state information input section 34. The method of calculating the functional error rate will be described later.

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

[0047] In step S13, the function error rate calculation unit 35 calculates the amount of change in the function error rate 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 operation settings and programs based on the change over time in the error rate calculated in step S13, and outputs the calculation result of the error correlation to the execution order adjustment unit 37.

[0049] In steps S9 and S14, the results of sorting may be held in the error correlation calculation unit 36 ​​and then output, or the results of sorting 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] <<Post-error correlation calculation processing>> After calculating the error correlation by the above procedure, in step S15, the execution order adjustment unit 37 selects the operation settings and programs to be executed while the evaluation target 2 is irradiated with radiation in accordance with the contents of the optimization rule memory 37a, and sends the result to the evaluation target control unit 38. For example, the order is changed so that functions with a low frequency of functional errors are executed with priority, and the cumulative amount of neutrons over irradiation time is 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 is low, and the reliability of the evaluation is 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] <Hardware Configuration of Soft Error Rate Evaluation Device 3> Next, an example of the hardware configuration of the soft error rate evaluation device 3 will be described with reference to Fig. 3. As shown in Fig. 3, 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 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 according to TCP / IP (Transmission Control Protocol / Internet Protocol) is adopted, but the present invention is not limited thereto, and communication according to 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 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 execute various types of processing by the processor 101 executing these programs.

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

[0059] <Data configuration example> 4A to 4D show examples of the collected data and error rate calculation progress data. Each figure will be explained in detail below.

[0060] <<Soft error database DB1>> Fig. 4A shows an example of the configuration of soft error database DB1. In this example, the name of the program executed on evaluation target 2 is used as the 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 the 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 holds 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 the calculation formula for the average soft error rate is shown in Equation 1.

[0062]

number

[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 predetermined from the specifications of the particle accelerator 11 and the evaluation target 2, and are stored in the soft error rate calculation unit 32 before the start of the test.

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

[0066]

number

[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 value of the particle accelerator 11 corrected for the distance from the target 4, and is set in advance. f This is the number of error events in the configuration example of the functional error database DB2.

[0068] <<SDCデータベース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, similar to the functional error database DB2.

[0069] <<Error rate time series table DB4>> Fig. 4D shows an example of the configuration of a time series table DB4 that records the time changes in the error rate in the soft error database DB1 and the functional error database DB2 (or the SDC database DB3). The average error rate of each database above stores the latest value, but the time series table DB4 stores the average error rate calculation results along the elapsed 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] <Convergence process of soft error rate> 5 shows the program of the present invention and the convergence process of error rate calculation. An example is shown in which programs P1, P2, and P3 are executed in order as a test program P that defines the operation when performing an accelerated test by irradiating radiation to an evaluation object 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] Figures 5(a) and (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. In this case, the error occurrence interval follows a Poisson distribution, so the soft error rate during the execution of each program should converge to an error rate according to the circuit scale and integration level of the logic device used in that program. Therefore, when evaluating the soft error rate by 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] FIG. 5(a) shows the convergence of the soft error rate when accelerated tests of programs P1, P2, and P3 are performed at equal time ratios. In this example, the soft error rates of programs P2 and P3 converge relatively quickly, while program P1 takes the longest to converge. In other words, FIG. 5(a) shows that the error occurrence intervals of the logic devices used in programs P2 and P3 are relatively short, and the error occurrence intervals of the logic device used in program P1 are relatively long. Therefore, in this example, it is necessary to continue the accelerated test until the error rate of program P1 converges.

[0073] On the other hand, FIG. 5(b) shows the effect of adjusting the execution order and execution time ratio of the programs according to this embodiment. In this example, the execution time ratio of the program P1, which was found to have the longest error occurrence interval by the test of FIG. 5(a), is increased (+30% in the example of FIG. 5(c)). Similarly, the execution time ratio of the program P2, which was found to have a longer error occurrence interval than the program P3 by the test of FIG. 5(a), is also increased to some extent (+10% in the example of FIG. 5(c)). In this way, by setting the execution time ratio of each program so as to be approximately inversely proportional to the error occurrence interval of each program, the time required for accumulating error events of the programs P1 and P2 is shortened, and the time required for accumulating error events of the program P3 is equalized, thereby shortening the time required for completing the accelerated test compared to the example of FIG. 5(a). Note that FIG. 5 describes a method for shortening the time required for the accelerated test to evaluate the soft error rate, but a similar method may be adopted when shortening the time required for the accelerated test to evaluate the functional error rate.

[0074] <An example of a mechanism for detecting functional errors> 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 embodiment, a mechanism is provided that outputs a soft error detection signal to the outside of the LSI when a soft error is detected in the logic LSI 61. Most general LSIs have a built-in mechanism for detecting soft errors even in actual use, and this embodiment is also equipped with a similar mechanism.

[0075] Even if a soft error occurs in the logic LSI 61, it may not affect the function, and the soft error rate and the 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 uses a comparator 64 to compare the output of the logic LSI 61 with an expected value stored in an expected value memory 63, and if they do not match, outputs a functional error detection signal. Although this example shows a configuration example focusing on the basic concept of functional error detection, it is necessary to separately consider the synchronization between the operation sequence of the logic LSI 61 and the expected value.

[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 error detection function may be implemented in 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 modified example 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 defect occurs during normal operation of the evaluation target 2, the comparison result information stored in the comparison result storage database 66 can be used to compare with the functional error occurrence pattern of the evaluation target 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, the program executed during the irradiation test may be run immediately after the functional error occurs, and the occurrence pattern of the functional error may be observed and compared with the stored data.

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

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

[0082] <Effects of this embodiment> The present embodiment described above makes it possible to improve 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 generators such as accelerators. EXAMPLES

[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 amount change instruction unit 39 is added to the soft error rate evaluation device 3, and beam amount change instruction data can be transmitted from the beam amount change instruction unit 39 to the accelerator control device 12 of the radiation irradiation facility 1.

[0084] In the case where the number of error events stored in the soft error database DB1 by the procedure of the first embodiment is less than a predetermined threshold value, or where the time series table of FIG. 4D is searched and it is recognized that the convergence of the soft error rate is slow, in this embodiment, 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, in the case where the number of error events stored in the soft error database DB1 by the procedure of the first embodiment is too many, or where the time series table of FIG. 4D is searched and it is recognized that the convergence of the soft error rate is too fast, it is possible that the errors are not properly evaluated, so 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 the 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 burden by reducing the energy consumption of radiation generation facilities such as accelerators.

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

[0087] In addition, each of the configurations, functions, processing units, processing means, etc. of the soft error rate evaluation device 3 may be realized in hardware, for example, by designing a part or all of them as an integrated circuit. In addition, each of the configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. Information such as a program, table, file, etc. that realizes each function can be stored in a memory, a recording device such as a hard disk or SSD, or a recording medium such as an IC card, an SD card, or a DVD. In addition, the control lines and information lines shown are those that are considered necessary for explanation, and not all control lines and information lines are necessarily shown in the product. In reality, it may be considered that almost all of the configurations are connected to each other. [Explanation of symbols]

[0088] 1. Radiation equipment, 11 particle accelerator, 12 Accelerator control device, 13 Target metal, 2. Evaluation subject, 3. Soft error rate evaluation equipment, 31 soft error signal input unit, 32 Soft error rate calculation unit, 33 Functional error signal input section, 34 Execution status information input section 35 Functional error rate calculation unit, 36 Error correlation calculation unit, 37 Execution order adjustment unit, 37a Optimization rule memory, 38 Evaluation target control unit, 39 Beam amount change instruction unit, DB1 Soft Error Database, DB2 Functional Error Database, 100 calculator, 101 processors, 102 Main storage, 103 Auxiliary storage, 104 Communication devices, 105 output device, 106 Input Devices

Claims

1. A method for evaluating a soft error rate of an electronic device irradiated with radiation, comprising the steps of: a radiation exposure step of irradiating radiation to an electronic device executing a test program that defines a combination of operations or functions to be used; a soft error detection step of detecting a soft error that occurs in the electronic device when exposed to radiation; a soft error rate calculation step of calculating a soft error rate based on the detection result of the soft error; 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 having a low error frequency from the plurality of test programs after performing the soft error detection step through the soft error rate change amount calculation step for each of the plurality of test programs, and adjusting the execution time ratio of the test program having a low error frequency so as to be large; a control step of controlling the electronic device to execute each of the plurality of test programs at an adjusted execution time ratio; 1. A method for evaluating a soft error rate comprising:

2. The soft error rate evaluation method according to claim 1, further comprising: a functional error detection step of detecting a functional error occurring in the electronic device; a function error rate calculation step of calculating a function error rate based on the detection result of the function error; A function error rate change calculation step of calculating a change in the function error rate, a step of adjusting the execution time ratio of each of a plurality of test programs, the step of detecting a functional error through the step of calculating a change in functional error rate being performed for each of the plurality of test programs, and then a test program having a low error frequency is extracted from the plurality of test programs, and an adjustment is made so that an execution time ratio of the test program having a low error frequency is increased.

3. 3. The method for evaluating a soft error rate according to claim 2, The soft error rate evaluation method, wherein the functional error is detected in the functional error detection step 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 method for evaluating a soft error rate, comprising: a radiation dose instruction generation 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 less than a predetermined threshold.

5. 2. A program for causing a computer to execute the steps of detecting a soft error through calculating a change in soft error rate, adjusting the execution time ratio, and controlling, according to claim 1.

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

7. A soft error rate evaluation apparatus for evaluating a soft error rate of an electronic device irradiated with radiation by a radiation irradiation facility, comprising: a soft error detection unit that detects a soft error that occurs in an electronic device when the electronic device is irradiated with radiation while executing a test program that defines a combination of operations or functions to be used; a soft error rate calculation unit that calculates a soft error rate based on the detection result of the soft error; a soft error rate change amount calculation unit for calculating the amount of change in the soft error rate; an execution time ratio adjustment unit that performs the calculation of the soft error rate change amount from the detection of the soft error for each of a plurality of test programs, extracts a test program having a low error frequency from the plurality of test programs, and adjusts the execution time ratio of the test program having a low error frequency so as to be large; a control unit that controls the electronic device so as to execute each of the plurality of test programs at an adjusted execution time ratio; 1. A soft error rate evaluation device comprising:

8. 8. The soft error rate evaluation device according to claim 7, further comprising: a functional error detection unit that detects a functional error occurring in an electronic device when the electronic device is executing the test program and the electronic device is irradiated with radiation; a functional error rate calculation unit that calculates a functional error rate based on the detection result of the functional error; a functional error rate change amount calculation unit for calculating a change amount of the functional error rate, the execution time ratio adjustment unit executes the calculation of the amount of change in functional error rate from the detection of the functional error for each of a plurality of test programs, extracts a test program having a low error frequency from the plurality of test programs, and adjusts the execution time ratio of the test program having a low error frequency so as to be larger.

9. 9. The soft error rate evaluation device according to claim 8, The soft error rate evaluation device, 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. 8. The soft error rate evaluation device according to claim 7, further comprising: a radiation dose instruction generation unit that generates an instruction to increase the radiation dose irradiated by the radiation irradiation equipment when the error frequency during execution of the test program is lower than a predetermined threshold.

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