Measuring Semaphore wait times with Micrometer - micrometer

We have a throttling implementation that essentially boils down to:
Semaphore s = new Semaphore(1);
...
void callMethod() {
s.acquire();
timer.recordCallable(() -> // call expensive method);
s.release();
}
I would like to gather metrics about the impact semaphore has on the overall response time of the method. For example, I would like to know the number of threads that were waiting for acquire, the time spend waiting etc., What, I guess, I am looking for is guage that also captures timing information?
How do I measure the Semphore stats?

There are multiple things you can do depending on your needs and situation.
LongTaskTimer is a timer that measures tasks that are currently in-progress. The in-progress part is key here, since after the task has finished, you will not see its effect on the timer. That's why it is for long running tasks, I'm not sure if it fits your use case.
The other thing that you can do is having a Timer and a Gauge where the timer measures the time it took to acquire the Semaphore while with the gauge, you can increment/decrement the number of threads that are currently waiting on it.

Related

Maximum number of tasks supported in AUTOSAR

What is the maximum number of tasks supported in AUTOSAR compliant systems?
In Linux, I can check the maximum process IDs supported to get the maximum number of tasks supported.
However, I couldn't find any source that states the maximum number of tasks supported by AUTOSAR.
Thank you very much for your help!
Well, we are still in an embedded automotive world and not on a PC.
There is usually a tradeoff between the number of tasks you have and what it takes to schedule them and what RAM/ROM and runtime resources your configuration uses.
As already said, if you just need a simple timed loop with some interrupts in between, one task may be ok.
It might be also enough, to have e.g. 3 tasks running at 5ms, 10ms and 20ms cycle. But you could also schedule this in simple cases like this with a single 5ms task:
TASK(TASK_5ms)
{
static uint8 cnt = 0;
cnt++;
// XXX and YYY Mainfunctions shall only be called every 10ms
// but do a load balancing, that does not run 3 functions every 10ms
// and 1 every 5ms, but only two every 5ms
if (cnt & 1)
{
XXX_Mainfunction_10ms();
}
else
{
YYY_Mainfunction_10ms();
}
ZZZ_Mainfunction_5ms();
}
So, if you need something to be run every 5, 10 or 20ms, you put these runnables into the corresponding tasks.
The old OSEK also had a notion of BASIC vs EXTENDED Tasks, where only extended tasks where able to react on OsEvents. This tasks might not run cyclically, but only on configured OsEvents. You would have an OS Waitpoint there, where the tasks is more or less stopped and only woken up by the OS on the arrival of an event. There are also OSALARM, which could either directly trigger the activation of a OsTask, or indirectly over an Event, so, you could e.g. wait on the same Waitpoint on both a cyclic event from an OsAlarm or an OsEvent set by something else e.g. by another task or from an ISR.
TASK(TASK_EXT)
{
EventMaskType evt;
for(;;)
{
WaitEvent(EVT_XXX_START | EVT_YYY_START | EVT_YYY_FINISHED);
GetEvent(TASK_EXT, &evt);
// Start XXX if triggered, but YYY has reported to be finished
if ((evt & (EVT_XXX_START | EVT_YYY_FINISHED) == (EVT_XXX_START | EVT_YYY_FINISHED))
{
ClearEvent(EVT_XXX_START);
XXX_Start();
}
// Start YYY if triggered, will report later to start XXX
if (evt & EVT_YYY_START)
{
ClearEvent(EVT_YYY_START);
YYY_Start();
}
}
}
This direct handling of scheduling is now mostly done/generated within the RTE based on the events you have configured for your SWCs and the Event to Task Mapping etc.
Tasks are scheduled mainly by their priority, that's why they can be interrupted anytime by a higher priority taks. Exception here is, if you configure your OS and tasks to be not preemptive but cooperative. Then it might be necessary to also use Schedule() points in your code, to give up the CPU.
On bigger systems and also on MultiCore systems with an MultiCore OS, there will be higher nunbers of Tasks, because Tasks are bound to a Core, though the Tasks on different Cores run independently, except maybe for the Inter-Core-Synchronization. This can also have a negative performance impact (Spinlocks can stop the whole system)
e.g. there could be some Cyclic Tasks for normal BaseSW components and one specific only for Communication components (CAN Stack and Comm-Services).
We usually separate the communication part, since they need a certain cycle time like 5..10ms, since this cycle is used by the Comm-Stack for message transmission scheduling and also reception timeout monitoring.
Then there might be a task to handle the memory stack (Ea/Fls, Eep/Fee, NvM).
There might be also some kind of Event based Tasks to trigger certain HW-control and processing chains of measured data, since they might be put on different cores, and can be scheduled by start or finished events of each other.
On the other side, for all your cyclic tasks, you should also make sure, that the functions run within such task do not run longer than your task cycle, otherwise you get an OS Shutdown due to multiple activation of the same task, since your task is started again, before it actually finished. And you might have some constraints, that require some tasks to finish in your applications expected measurement cycle.
In safety relevant systems (ASIL-A .. ASIL-D) you'll also have at least one task fpr each safety-level to get freedome-from-interference. In AUTOSAR, you already specify that on the OSApplication which the tasks are assigned to, which also allows you to configure the MemoryProtection (e.g. WrAccess to memory partitions by QM, ASIL-A, ASIL-B application and tasks). That is then another part, the OS has to do at runtime, to reconfigure the MPU according to the OsApplications MemoryAccess settings.
But again, the more tasks you create, the higher the usage of RAM, ROM and runtime.
RAM - runtime scheduling structures and different task stacks
ROM - the actual task and event configurations
Runtime - the context switches of the tasks and also the scheduling itself
It seems to vary. I found that ETAS RTA offers 1024 tasks*, whereas Vector's MICROSAR OS has 65535.
For task handling, OSEK/ASR provides the following functions:
StatusType ActivateTask (TaskType TaskID)
StatusType TerminateTask (void)
StatusType Schedule (void)
StatusType GetTaskID (TaskRefType TaskID)
StatusType GetTaskState (TaskType TaskID, TaskStateRefType State)
*Link might change in future, but it is easy to search ETAS page directly for manuals etc.: https://www.etas.com/en/products/download_center.php
Formally you can have an infinite number of OsTasks. According to the spec. the configuration of the Os can have 0..* OsTask.
Apart from that the (OS) software uses data type TaskType for Task-Index variables. Therefore, if TaskType is of uint16 you could not have more than 65535 tasks.
Besides that, if you have a lot of tasks, you might re-think your design.

FreeRTOS suspend task from another function

So I have a half duplex bus driver, where I send something and then always have to wait a lot of time to get a response. During this wait time I want the processor to do something valuable, so I'm thinking about using FreeRTOS and vTaskDelay() or something.
One way to do it would off be splitting the driver up in some send/receive part. After sending, it returns to the caller. The caller then suspends, and does the reception part after a certain period of time.
But, the level of abstraction would be finer if it continues to be one task from the user point of view, as today. Therefore I was thinking, is it possible for a function within a task to suspend the task itself? Like
void someTask()
{
while(true){
someFunction(&someTask(), arg 1, arg 2,...);
otherStuff();
}
}
void someFunction(*someSortOfReferenceToWhateverTaskWhoCalled, arg1, arg2 ...)
{
if(something)
{
/*Use the pointer or whatever to suspend the task that called this function*/
}
}
Have a look at the FreeRTOS API reference for vTaskSuspend, http://www.freertos.org/a00130.html
However I am not sure you are going about controlling the flow of the program in the correct way. Tasks can be suspended on queues, events, delays etc.
For example in serial comms, you might have a task that feeds data into a queue (but suspends if it is full) and an interrupt that takes data out of the queue and transmits the data, or an interrupt putting data in a queue, or sending an event to a task to say there is data ready for it to process, the task can then wake up and process the data or take it out of the queue.
One thing I think is important though (in my opinion) is to only have one suspend point in any task. This is not a strict rule, but will make your life a lot easier in most situations.
There a numerous other task control mechanisms that are common to most RTOS's.
Have a good look around the FreeRTOS website and play with a few demo's. There is also plenty of generic RTOS tutorials on the web. It it worth learning how use the basic features of most RTOS's. It is actually not that complicated.

How can I improve performance with FutureTasks

The problem seems simple, I have a number (huge) of operations that I need to work and the main thread can only proceed when all of those operations return their results, however. I tried in one thread only and each operation took about let's say from 2 to 10 seconds at most, and at the end it took about 2,5 minutes. Tried with future tasks and submited them all to the ExecutorService. All of them processed at a time, however each of them took about let's say from 40 to 150 seconds. In the end of the day the full process took about 2,1 minutes.
If I'm right, all the threads were nothing but a way of execute all at once, although sharing processor's power, and what I thought I would get would be the processor working heavily to get me all the tasks executed at the same time taking the same time they take to excecuted in a single thread.
Question is: Is there a way I can reach this? (maybe not with future tasks, maybe with something else, I don't know)
Detail: I don't need them to exactly work at the same time that actually doesn't matter to me what really matters is the performance
You might have created way too many threads. As a consequence, the cpu was constantly switching between them thus generating a noticeable overhead.
You probably need to limit the number of running threads and then you can simply submit your tasks that will execute concurrently.
Something like:
ExecutorService es = Executors.newFixedThreadPool(8);
List<Future<?>> futures = new ArrayList<>(runnables.size());
for(Runnable r : runnables) {
es.submit(r);
}
// wait they all finish:
for(Future<?> f : futures) {
f.get();
}
// all done

Kthread and Schedule() slowing down the code. OR how to sleep in kernel

Using module_init I have created and woken up a kthread. In order to keep it alive and also do my function task, I used the following approach. That was the only approach I could make it running since I am changing the flag in an interrupt. Now I am facing an unbelievably drop in the performance of the code. I narrowed down a problem to the following piece of code:
while(1){
//Do my tasks here after changing flag
while(get_flag() ){ //Waiting for a flag, to basically do my Func in the previous line.
schedule();
}
}//to keep a kthread alive after initial create.
Details about dropping the performance: without using the second while(1) which includes schedule, the rate of data transmission in my code is 35MB/s but with this little line, it drops to 5MB/s.
Is there any other way that I can make a kthread sleep and wait for a flag change?
Ideally, This is not the way you should do this in Kernel. But if you have to do it this way.
See if you are doing a blocking check for the flag? If that is the case, change it to non-blocking wait, just check for the flag and schedule that should be enough in most of the cases. The scheduling algorithm will make sure to get the fair share of CPU for all the processes. Also, if you are doing a blocking check for flag you are unnecessarily wasting CPU cycles since you are doing the processing only on the next scheduler slice. with the same logic, if you want to get better performance, you should wake up your waiting process from your producer thread with wakeup_task()
-or-
if you just want to achieve the functionality, I feel the right way to do it is the following method. using a wait queue, wait_even_interruptible() and wake_up_interruptible()
From your above said kernel thread you just need to call the wait_event_interruptible
see the pseudo code below
while (1){
wait_event_interruptible(wq, your_flag)
{
<do your task>
}
}
and from the place you are setting the flag
{
<some event>
<set flag>
wake_up_interruptible (wq)
}
You don't have to call the schedule explicitly.

context switch measure time

I wonder if anyone of you know how to to use the function get_timer()
to measure the time for context switch
how to find the average?
when to display it?
Could someone help me out with this.
Is it any expert who knows this?
One fairly straightforward way would be to have two threads communicating through a pipe. One thread would do (pseudo-code):
for(n = 1000; n--;) {
now = clock_gettime(CLOCK_MONOTONIC_RAW);
write(pipe, now);
sleep(1msec); // to make sure that the other thread blocks again on pipe read
}
Another thread would do:
context_switch_times[1000];
while(n = 1000; n--;) {
time = read(pipe);
now = clock_gettime(CLOCK_MONOTONIC_RAW);
context_switch_times[n] = now - time;
}
That is, it would measure the time duration between when the data was written into the pipe by one thread and the time when the other thread woke up and read that data. A histogram of context_switch_times array would show the distribution of context switch times.
The times would include the overhead of pipe read and write and getting the time, however, it gives a good sense of big the context switch times are.
In the past I did a similar test using stock Fedora 13 kernel and real-time FIFO threads. The minimum context switch times I got were around 4-5 usec.
I dont think we can actually measure this time from User space, as in kernel you never know when your process is picked up after its time slice expires. So whatever you get in userspace includes scheduling delays as well. However, from user space you can get closer measurement but not exact always. Even a jiffy delay matters.
I believe LTTng can be used to capture detailed traces of context switch timings, among other things.

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