Every time I dip my toes in multithreading in C++, I just get into a world of random crashes and segfaults. It seems unreasonably hard, hah.
A good book to study and get a handle on all aspects of Concurrent Programming is Foundations of Multithreaded, Parallel, and Distributed Programming by Gregory Andrews - https://www2.cs.arizona.edu/~greg/mpdbook/
Even Rich Hickey, when discussing concurrency in Java/C#/C++ said "I am tired of trying to get right, because it is simply far too difficult."
> In particular, talk about shared state, how we do it today, how you do it in C#, Java, or C++, what happens when we get into a multi-threaded context, and specifically what are some of the current solutions for that in those spaces. Locking, in particular. That is something I have done a lot of, over a long period of time, and I am tired of trying to get right, because it is simply far too difficult.
( https://github.com/matthiasn/talk-transcripts/blob/master/Hi... )
The second point to note is that when people like Rich Hickey or John Ousterhout talk about multi-threaded programming being "hard" they are talking about a level of depth far beyond what a "normal" application programmer will encounter in his/her entire career. These guys span everything from Apps/OS/Compilers/Language/Hardware and hence by necessity know the full gamut of complexity involved in concurrency. Trying to understand concurrency across all the above abstraction layers is very difficult and that is what they mean when they say it is "hard".
But for most application programmers the above is simply not relevant and they can comfortably stay at higher-level abstractions given by their language/library and ignore lower-level details unless and until forced by other needs like performance etc. One can do a lot with this knowledge alone and indeed that is what most of us do.
So instead of making wild statements like "random crashes and segfaults" and "too hard to program" learn to use heuristics/commonsense to simplify the code structure eg. a) copy code patterns given by reputed authors so one does not make unnecessary errors b) Keep the number of locks to a minimum by using a few "global locks" rather than a lot of "granular locks" c) Learn to use Thread Local Storage d) Acquire locks/resources in the same order to avoid deadlocks etc etc.
These three have different memory models, concurrency primitives and adopted practices...it's odd that they are lobbed together.
I strongly dislike the term "lock free", which is really just a marketing term invented by people trying to promote the idea that some algorithms are better than those "lock-based", when in fact those "lock-free" algorithms were only choosing a different trade-off in performance, which can be better or worse, depending on the application.
Even worse is that after the term "lock free" has become fashionable, it has also been applied to unrelated algorithms, so now it has become ambiguous, so you cannot know for sure what is meant by it, unless more details are provided.
When accessing shared data structures, the accesses are most frequently done in one of three ways.
The first is to use mutual exclusion, when the shared data structure is accessed within critical sections and only one thread can execute the critical section at a given time. This method is usually called as lock-based access.
The second is to use optimistic access, when the shared data structure is accessed concurrently by many threads, but they are able to detect interference from the other concurrent accesses and they retry their accesses in such cases. This is what is most frequently referred as "lock free" access. Compared to mutual exclusion, this access method may be faster in the best cases, but it is much slower in the worst cases, so whether this is a good choice depends on the application.
The third method happens when it is possible to partition the shared resource between the threads that access it concurrently, so their concurrent accesses can proceed without fear of interference. This partitioning is usually possible for arrays and for buffers a.k.a. FIFO memories a.k.a. message queues (including one-to-one, many-to-one, one-to-many and many-to-many message queues).
So your "lock free ringbuffer" refers to the third method from above, which is very different from the "lock free" algorithms of the second kind from above.
Whenever concurrent access to partitioned shared resources is possible, it is much better than accesses with mutual exclusion or optimistic accesses, which require either waiting or retrying, both of which are wasting CPU time.
Therefore using correctly-implemented message queues or other kinds of shared buffers is usually the best method to achieve high levels of concurrency, in comparison with other kinds of shared data structures, because it avoids the bottlenecks caused by mutual exclusion or optimistic accesses.
The alternative term "optimistic access" describes much better the essence of those algorithms, while "lock free" attempts to hide their nature and to make them look like something that is guaranteed to be better (so receiving money for researching them is justified), because locks are supposed to be bad.
"Lock free" and "wait free" have been buzzwords that have provided subjects for a huge number of research papers in the academia, most of which have been useless in practice, because the described algorithms have been frequently worse than the lock-based algorithms that they were supposed to replace.
They have a desirable property. If you needed a wait-free algorithm, and this is a wait-free algorithm it's not "worse" for you than an existing algorithm that isn't wait-free, regardless of whether it's slower, or more memory intensive or whatever. You needed wait-free and this is wait free.
Why is wait-free desirable? Well, unlike a lock-free algorithm, the wait-free algorithm makes progress in defined time for everybody and it might be that it's actually much worse if anybody is stalled than for the averages to be bad for example.
If you mean "fast on average" say that. If you mean (as often C++ programmer do) "Validates my feeling of self-worth" then say that. I don't know whether anybody wants to pay you more money to validate your self-worth, but at least you're being honest about your priorities.
Step 2: when you absolutely need concurrency within one app, try using some library that already solved the issue. For example, there are lots of databases with pretty strong concurrency contracts while still being efficient.
Step 3: if you absolutely need custom solution, use a library/language that provides reasonable tools out of the box and keep your logic to minimum.
Following the first two steps will solve 95% of your concurrency issues, if you include step 3 it goes to 99%.
So it was left to the developer. It is much better now but for so long the problem was ignored and now we have decades of 'not sure if I can touch that code'. Also by default C/C++ are fairly open about sharing memory. So it is very easy create race conditions on memory. It would be nice if the base language had a concept of 'locked to a thread' or 'i want to share this with other threads' then the compiler can flag where I have wandered into the weeds for a class so we could catch the race conditions at compile time, at least some sort of warning.
Sharing semantics were awful for a long time. stdlib has done some very good things to help clean that up but it is still very easy to share between threads and cause yourself a headache.
The problem with an owning mutex in such a language is that you can (on purpose or by mistake) keep accessing the thing it owned after you've released the protecting mutex. Rust's Mutex<T> owns the T but it has the behaviour you want where if you tried to keep the access to T but give back the mutex that doesn't compile. "I tried to unlock the mutex but I still need it, d'oh".
And the same problem applies broadly, you should not share write access to things without an ordering guarantee, but it's hard to ensure that guarantee is followed in C++.
For heavy workloads, this approach doesn't scale particularly very well.
If there is no shared ownership then inventing it so as to make your Rust slower is just a problem with you, not with Rust.
[1] https://bholley.net/blog/2015/must-be-this-tall-to-write-mul...