What are the common RTOS performance bottlenecks and how to avoid them?

Multiprocessing and Single Processing Systems: Systems and even smaller embedded have at least two cores now-a-days. AMP (Asynchronous) implementations use a different instance of RTOS on each core whereas SMP use one instance of RTOS. Task Ready Queues are different in AMP and same ready queue for SMP. But we have programming/configuration constructs which give core preference option to run the task. In SMP systems, same scheduler code section needs to be executed by each core, the code and data resides in one same memory so some cases the CPU cores of the RTOS compete with each other. Identifying and assign proper task priorities, critical sections and contention/synchronization workflows in design of Tasks is important on RTOS.

Knowing when to be flexible: adding dynamic evaluation and modification of priority based on system state. With this in mind: adhering to the lessons in avoiding: excessive context switching, priority inversion, starvation, or missed deadlines. Introducing a fast hi-priority task, or low-level module, that adds a behavioral watchdog to gather simple metrics of other tasks status and check that they are in line with expected behavior. If not, do recovery to a safe but functional system state.

Effective task scheduling is crucial in RTOS. Here’s how I managed it: * Use Preemptive Scheduling: * Challenge: Poorly designed task scheduling can result in context switching, priority inversion, and missed deadlines. * Solution: Implement a preemptive scheduling algorithm to allow higher priority tasks to interrupt lower priority ones. * Example: Reduced the number of tasks and their priority levels to minimize complexity and overhead. * Avoid Blocking Tasks: * Challenge: Blocking tasks waiting for external events or resources can be inefficient. * Solution: Use non-blocking or asynchronous methods. * Example: Implemented rate monotonic analysis (RMA) to verify the schedulability of tasks.

A possible definition for ISR: the CPU instructions which your program will jump to when the associated interrupt occurs. Sometimes ISRs and interrupt triggered tasks are preferred over polling tasks because (1) they can be more responsive and (2) they do not use CPU cycles until they are triggered. But polling tasks can be preferable because of their predictability; they can be scheduled to run at a given period, instead of on every single occurrence of a certain event or interrupt, which can bound the maximum CPU cycles they use. Polling tasks scheduled periodically also make schedule analysis simpler.

Allocations from the heap may be slow, try avoid. If using C++ on embedded, it's easy enough to create a templated fixed_container<T,size> which won't incur any heap costs

I disagree that all dynamic allocation should be avoided. I think that fragmentation and leakage can be mitigated by avoiding HEAP allocation, not all dynamic allocation, like the stack. Heap allocation risks fragmentation and leakage which degrade program performance. On the other hand, stack memory is allocated and freed automatically, and the address of the next available frame is always known, thus avoiding the risks of the heap. Static memory is another alternative to the heap and avoids potential fragmentation and leaks.

Do yourself a favor and avoid dynamic memory allocation for embedded. The benefits that C++ leverages on an application processor, or an x86 machine do not scale well to Cortex M devices. The indexing latency, whether hardware assisted or not, will result in higher power consumption for the same amount of effectual work. This leads to reduced sleep time between macroscopic cycles. And this is never an equitable tradeoff in battery powered embedded projects, where every uW counts.

To avoid Inefficient Memory Management: Use memory pools, which allow for the allocation and deallocation of fixed-size blocks, to reduce fragmentation. Ensure that the system has sufficient memory for its peak load to avoid memory shortages.

Dynamic allocation is generally frowned upon with anything that needs to be safely certified. misra, do178b and I forget the medical one

Algo que se nota facilmente quando se come?a a estudar os diversos RTOS que est?o disponíveis para se trabalhar com sistemas embarcados é a similaridade deles no quesito de comunica??o entre tarefas. FreeRTOS (agora com um port disponível para a AWS, da AMAZON), Zephyr, AzureRTOS, uOS-II (só para ficar entre os quatro mais usados mundialmente em projetos com RTOS): todos eles apresentam recursos para troca de mensagens entre as tarefas, como os semaforos, os mutexes, pilhas de flag, memória compartilhada, etc. Isso permite que uma tarefa feita para um periférico A (uma porta serial, por exemplo), possa conversar com um periférico B (um conversor ADC, por exemplo).

To implement Inter-task communication effectively, it's crucial to choose the right communication mechanism for the specific requirement, ensuring that tasks interact seamlessly without introducing bottlenecks or inconsistencies. Properly designed inter-task communication can greatly improve the efficiency, responsiveness, and reliability of a multitasking system.

Best Practices for Inter-Task Communication in RTOS: 1 Choose the Right Communication Method: * Use message queues, semaphores, mutexes, pipes, or shared memory based on specific needs. * Example: Minimized data transfer amount and frequency to reduce overhead. 2 Implement Synchronization Mechanisms: * Prevent deadlock or priority inversion with protocols like priority inheritance or ceiling protocols. ?Optimizing inter-task communication is key to a responsive and efficient RTOS. What methods do you use for inter-task communication?