las3_pub / predictable_parallel_patterns

It is still not working, however we now have no more redundant code, making debugging it simpler.

We changed up some of the memory constraints in the lock free deque and will need to see if this is ok. If so, the single threaded performance looks very good.

Everything so far is untested. We only made sure tha fast path still seems to function correctly. Next up is writing tests for both the fast and slow path to then introduce the slow path. After that we can look at performance optimizations.

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.

This first sketch of the classes captures what we think is needed in terms of general interface and very mich WIP.

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).

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.

This makes the programming model a full dataflow implementation, as it allows for branching and recursion.

Recursion works by using a function node, calling the graph again. We separated an graph invocation form an function invocation within an graph, making the graph only handle one concern.

We separated the structure (input-output flow) from the rest of the architecture and reworked some template programming to have better access to the types required at compile time.

The data can now flow into a graph, follow its path on inptus/outputs and be fetched from the graph after execution.
Currently graphs are executed synchronous.

We need some tricks in template programming to have a clean user facing API while internally using our classes with more capabilities.

This is the base building block for creating the actual dataflow functions and networks, as their main functionality is having data flow through connected nodes.

This removes boost as an dependency from our code and makes our project
again only dependent on C++11 compilers (no external dependency).

Now all algorithms are used without the parallel pre-/suffix and the for_each method has an specialization for integer ranges.

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

These currently do nothing but being boilerplate required to implement a new top level 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.