Consider the case where a triggered Model block is configured to run in the SIL or PIL simulation mode. The software generates one execution-time measurement each time the referenced model is triggered to run. If there are multiple triggers in a single time step, the software generates multiple measurements for the triggered Model block. Conversely, if there is no trigger in a given time step, the software generates no time measurements.
When you run a SIL simulation with execution time profiling enabled, you might see spikes in execution-time measurements.
The spikes are due to process preemption that occurs with a multitasking host operating system. If the operating system preempts the SIL process and runs another process, the measured execution time includes the time during which the SIL process is suspended. With a PIL simulation, you do not see spikes because code execution on the target is not preempted.
Counter wrapping produces execution-time measurements that are smaller than expected. For SIL, the counter wraps when an execution-time period is greater than 264 ticks (232 ticks if the MEX compiler is LCC). For PIL, the wrapping point depends on the timer you specify and can be 28, 216, 232, or 264 ticks.
Consider a PIL example where the timer frequency is 20 MHz. For a 32-bit timer, wrapping
occurs when the execution-time period is greater than
that is, 214.7 s. However, for a 16-bit timer, the point at which wrapping occurs is 0.0033
For a real-time, multi-core application, the software accommodates synchronization discrepancies when recording timer values for different cores, which effectively reduces the timer measurement range.
If your target configuration does not already specify a timer, create a timer object that provides details of the hardware-specific timer and associated source files:
For SIL simulation, the timer word length is 64 bits.
For PIL simulation, you can specify an 8-, 16-, 32-, or 64-bit timer.
Profiling instrumentation is intrusive and affects the quantity that it is meant to measure. Therefore, the design goal is to maximize code understanding with a minimum of instrumentation. For example, with a real-time system, there can be task context switches due to preemption. These context switches are not explicitly instrumented. To record the start and end of each task, the software must infer context switches from instrumentation. As a result, the software reports behavior that is an estimate. The estimate is subject to error because of incomplete instrumentation within the kernel.
In some cases, when the software cannot accurately determine behavior, the software generates a warning:
Warning: Analysis unsuccessful for one or more profiling data points. ...
set_param(model, 'CodeProfilingInstrumentation', 'on')). If a mutex take system call is not instrumented, a task context switch might occur that is not visible to the execution profiling analysis.
In other cases, although the software cannot accurately determine behavior, the software does not generate a warning.
You cannot generate execution-time profiles for function call sites within subsystem code that is reused across a model or multiple models. For information about subsystem code reuse, see Generate Reusable Code from Library Subsystems Shared Across Models.
You cannot load execution-time measurements saved with a previous release. For example, using R2014a, you save workspace variables to a MAT-file. One of the workspace variables contains execution-time measurements. In R2015b, if you try to load the MAT-file, you see this error:
Format of execution profiling data is invalid. This error can occur if you load data from a previous release. Loading data from a previous release is not supported.