las3_pub / predictable_parallel_patterns

Currently once we are serial no more parallel strains are executed. However, this could be changed using strain local resources in the future.

The strain_local resources can be used to get unique IDs for resources that would, in a serial execution, only be used once in the call chain. This is a first prototype implementation and needs further tesitng. The current implementation adds linear overhead to each steal proportional to the number of used  resources. We might be able to reduce it, but for a first version it is fine.

The flag can be used to run code annotated with PLS outside of a scheduler environment,
i.e. the app does not crash if the code is called without context. The compile option
allows to omit all spawn and sync calls during compilation, creating the equivalent serial code.

Add key-points required to capture an execution DAG. Currently all data is in-memory and printed out. In future work it would be good to store the DAG's and/or process them further.

Remove easy profiler for now. It might be useful for later on to get a grasp of general behaviour, but because of its issues with coroutines it is not worth profiling code with it right now.

I am not sure if this is appropriate, but it works and is no focus of this project.

It is now possible to use a memory mapped stack that throws a SIGSEV if thes coroutine stacks are exhausted.

Remove the strict static memory allocation scheme in favour of placing objects on the heap at startup. This still keeps the requirements posed for modern, high performance embedded systems, but makes APIs a lot cleaner.

The project is currently really messy and there are sporadic sigsevs. This indicates that we still have a race in our code. Thread Sanitizer does not work with our current implementation, as it needs annotations for fibers.

The next step is to clean up the project and maybe add thread sanitizer support to our fiber implementation. This should help finding the remaining bugs.

The current state shows the minimum actions taken to execute a parallel call: get the thread local, find the active frame, execute on the next frame and return to the active frame.

This showcases the expected performance when a task executes a sub-tree without inference from other threads. We target to stay about 6x slower than a normal function call.

We changed how the memory is allocated from passing char* buffers to then store objects into to creating 'fat objects' for all scheduler state. This eases development for us, as we can make changes to data structures without too much effort (e.g. add a second array to manage tasks if required).

This allows us to more easily handle them and makes their interface closer to std::thread.

The scheduler yields if it failed to steal any work due to the task
lists being empty. This should improve performance on multiprogrammed
systems, as it potentially makes room for other worker threads which
still have work to perform.

Threads must be joined on scheduler termination and tasks must be pushed onto the stack to allow better memory management.

This should have been fine without the atomic property (as it is only a single writer and multiple readers to a single bit). Nevertheless we fixed the 'race' to remove a warning in the thread sanitizer.

Please note that this does currently not execute, but only removed the 'old aspecs'. We are still missing launching the root fork_join task.

We do this to properly separate the cache alginment logic in the next step, allowing us to port all cache aligned objects without worrying about portability.

We do so by pulling out the profiling macros in our own iclude file. In the future we might even be able to use this to build up further visualisations of the executing programm.

This lead to some bug-fixes that covered move constructors not correctly assigning memory. We might clean this up further by only allowing in place creation of these types (placement new).

There are serval ways we could optimize the calls, but for now this should be enough for first tests.