Operating Systems 2017F Lecture 10
Video
Video from the lecture given on October 10, 2017 is now available. (The audio worked!)
Notes
In-Class
Lecture 10 ---------- Concurrency - more than one thing happening at the same time challenge with concurrency is keeping shared state consistent * files that are written to by multiple processes * two or more processes communicating * multiple threads within a process concurrency leads to race conditions - order of interleaved actions affects output - ex. did process A or B modify the file first? We want deterministic behavior from concurrent computations To get consistent computation, we need to coordinate - but you can't interact via regular variables Regular variables are subject to the memory hierarchy - variables are stored in registers, L1 cache, L2 cache, L3 cache, main memory - can be deeper in some contexts - so what if coordination variable is in L1 cache for one thread and in main memory for another? - hardware maintains consistency...eventually mechanisms for coordinating concurrent computations must bypass the memory hierachy Instead use - filesystem locking primitives (kernel) - special machine language instructions Operating systems - kernels in particular - are highly concurrent - makes them painful to code - have to always worry about having exclusive (or safe) access to data, resources Abstractions for managing concurrency - atomic variables guarantee strict ordering of operations Example Variable X: ***** <- range of memory locations To modify X, you... - load X into a register - modify the register - save the register to X What if two cores try to modify X at the same time? - both could have X in a register at the same time X is 5 core A increments by 1 core B decrements by 1 What's X after both have run? If B changes X but doesn't see A's change...you get 4 If A changes X but doesn't see B's change...you get 6 For X to be atomic, ^^^ shouldn't be possible - has to make sure only one core accesses X at a time Atomic variables are typically used to build semaphores... But what we really want is mutual exclusion - only one thread/process/CPU can access the resource at a time Want mutual exclusion for larger resources, e.g. data structures, devices Higher-level languages directly support mutual exclusion, e.g. Java synchronized methods Semaphores are an analogy to a railroad control mechanism - only one train on the track! When a train enters the shared track - grab the semaphore (increment atomic variable) - if not available, wait (check first to see if it is 0) When a train leaves the shared track - release the semaphore (decrement atomic variable) Lesson: don't implement semaphores yourself, please! In the Linux kernel - locks using semaphores of various types are associated with all kinds of data structures e.g. inodes When you can't get the lock, what do you do? - sleep (tell the scheduler to wake you up when the lock is available) - deal with not getting the resource - spin (do a null loop) If the wait time is short, spinning is the fastest thing you can do Where possible, everything should be exclusive, minimize sharing But in userspace... - shared memory...NOOOOOOO - unless you use atomic variable, or something higher level like a semaphore - messages - series of messages can be used to synchronize state 3-way handshakes, e.g. opening a TCP connection - SYN (synchronize) client->server - SYN-ACK (acknowledge SYN) server->client - ACK (acknowledge) client->server Can send messages between processes - signals! - other ways too concurrency pattern: producer/consumer * two processes P and C * P "makes" things, C "consumes" them * want to coordinate P and C - P shouldn't produce too much (C gets too far behind) - C shouldn't waste time waiting for P * shared circular buffer for storing output of P and input of C * when buffer is empty, C should sleep * when buffer is full, P should sleep