Class 8
CS 202
14 February 2024

On the board
------------

1. Last time
2. Deadlock
3. Other progress issues
4. Performance issues and tradeoffs
5. Programmability issues
6. Mutexes and interleavings

--------------------------------------------------------------------------

1. Last time

    - Advice and practice with concurrent programming
    - Multiple readers, one reader module
    - Implementation of spinlocks, mutexes
    
    Today: the problems in lock-based programming

2. Deadlock 

    --see handout: simple example based on two locks

    --see handout: more complex example

	    --M calls N 
	    --N waits
	    --but let's say condition can only become true if N is invoked
	    through M
	    --now the lock inside N is unlocked, but M remains locked; that
	    is, no one is going to be able to enter M and hence N.

    --can also get deadlocks with condition variables

    --lesson: dangerous to hold locks (M's mutex in the case on the
    handout) when crossing abstraction barriers

    --deadlocks without mutexes:

        real issue is resources and how/when they are required/acquired

        (a) [draw bridge example]

	    --bridge only allows traffic in one direction 

	    --Each section of a bridge can be viewed as a resource. 

	    --If a deadlock occurs, it can be resolved if one car
	    backs up (preempt resources and rollback). 

	    --Several cars may have to be backed up if a deadlock occurs. 

	    --Starvation is possible. 

	(b) another example:
		
	    --one thread/process grabs disk and then tries to grab
	    camera

	    --another thread/process grabs camera and then tries to
	    grab disk

    --when does deadlock happen? under four conditions. all of them must
    hold for deadlock to happen:

	1. mutual exclusion
	2. hold-and-wait
	3. no preemption
	4. circular wait


    --what can we do about deadlock?

        (a) ignore it: worry about it when it happens. the so-called
        "ostrich solution"

        (b) detect and recover: not great

	    --could imagine attaching debugger

		--not really viable for production software, but
		works well in development

	    --threads package can keep track of resource-allocation graph

	    --see one of the recommended texts:

		--For each lock acquired, order with other locks held 
		
		--If cycle occurs, abort with error 
	    
		--Detects potential deadlocks even if they do not occur 


        (c) avoid algorithmically

            [not covering]

	    --banker's algorithm (see Tanenbaum text for an desription)

		--very elegant but impractical

		--if you're using banker's algorithm, the gameboard
		looks like this:

		    ResourceMgr::Request(ResourceID resc,
					 RequestorID thrd) {
			acquire(&mutex);
			assert(system in a safe state);
			while (state that would result from giving 
			       resource to thread is not safe) {
			    wait(&cv, &mutex);	
			}
			update state by giving resource to thread
			assert(system in a safe state);
			release(&mutex);
		    }

		    Now we need to determine if a state is safe....

		    To do so, see book

	    --disadvantage to banker's algorithm:

		--requires every single resource request to go
		through a single broker

		--requires every thread to state its maximum
		resource needs up front. unfortunately, if threads
		are conservative and claim they need huge quantities
		of resources, the algorithm will reduce concurrency

        (d) negate one of the four conditions using careful coding:

	    --can sort of negate 1
		--put a queue in front of resources, like the printer
		--virtualize memory

	    --not much hope of negating 2

	    --can sort of negate 3:
		--consider physical memory: virtualized with VM, can
		take physical page away and give to another process! 

	    --what about negating #4?

		--in practice, this is what people do

		--idea: partial order on locks

		    --Establishing an order on all locks and making
		    sure that every thread acquires its locks in
		    that order

		--why this works:

		    --can view deadlock as a cycle in the resource
		    acquisition graph

		    --partial order implies no cycles and hence no
		    deadlock

		--two bummers:

		    1. hard to represent CVs inside this framework.
		    works best only for locks.

		    2. Picking and obeying the order on *all* locks
		    requires that modules make public their locking
		    behavior, and requires them to know about other
		    modules' locking.  This can be painful and
		    error-prone. 

			--see Linux's filemap.c example on the handout;
			this is complexity that arises by the need for a
			locking order

	(e) Static and dynamic detection tools

	    --See, for example, these citations, citations
	    therein, and papers that cite them:

		Engler, D. and K. Ashcraft. RacerX: effective,
		static detection of race conditions and deadlocks.
		Proc. ACM Symposium on Operating Systems Principles
		(SOSP), October, 2003, pp237-252.
		http://portal.acm.org/citation.cfm?id=945468

		Savage, S., M. Burrows, G. Nelson, P. Sobalvarro,
		and T. Anderson. Eraser: a dynamic data race
		detector for multithreaded programs. ACM
		Transactions on Computer Systems (TOCS), Volume 15,
		No 4., Nov., 1997, pp391-411.
		http://portal.acm.org/citation.cfm?id=265927

		a long literature on this stuff

	    --Disadvantage to dynamic checking: slows program down

	    --Disadvantage to static checking: many false alarms
	    (tools says "there is deadlock", but in fact there is
	    none) or else missed problems

	    --Note that these tools get better every year. I believe
	    that Valgrind has a race and deadlock detection tool


3. Other progress issues

    Deadlock was one kind of progress (or liveness) issue. Here are two
    others...

    Starvation

	--thread waiting indefinitely (if low priority and/or if
	resource is contended)

    Priority inversion

	--T1, T2, T3: (highest, middle, lowest priority)

	--T1 wants to get lock, T2 runnable, T3 runnable and holding lock

	--System will preempt T3 and run highest-priority runnable thread, namely T2

	--Solutions:

	    --Temporarily bump T3 to highest priority of any thread that is
	    ever waiting on the lock

	    --Disable interrupts, so no preemption (T3 finishes)
		... not great because OS sometimes needs control
		(not for scheduling, under this assumption, but for
		handling memory [page faults], etc.)

	    --Don't handle it; structure app so only adjacent priority
	    processes/threads share locks

	--Happens in real life. For a real-life example, see:
	https://www.microsoft.com/en-us/research/people/mbj/just-for-fun/
        (search for Pathfinder)

---

admin note:

Therac-25:
    - Wed Feb 19
    - required reading/class

---


4. Performance issues and tradeoffs

    (a) Implementation of spinlocks/mutexes can be expensive. Reasons:

        --mutex costs: 
            --the raw instructions required to execute "mutex_acquire"
            --going to sleep and waking up implies context switch, which
            brings a resource cost

        --spinlock costs:
            --cross-talk among CPUs 
            --cache line bounces
            --fairness issues
        
            --> this can be mitigated (if you're curious, look up
            "MCS locks").

    (b) Coarse locks limit available parallelism  ....

        [(still, you should design this way at first!!!)]

	    the fundamental issue with coarse-grained locking is that
	    only one CPU can execute anywhere in the part of your code
	    protected by a lock. If your critical section code is called
	    a lot, this may reduce the performance of an expensive
	    multiprocessor to that of a single CPU.

	    if this happens inside the kernel, it means that
	    applications will inherit the performance problems from the
	    kernel


    (c) ... but fine-grained locking leads to complexity and hence bugs
    (like deadlock)

        --> although finer-grained locking can often lead to better
        performance, it also leads to increased complexity and hence
        risk of bugs (including deadlock).

        --> see handout

5. Programmability issues

    Loss of modularity

	--examples above: avoiding deadlock requires understanding
	how programs call each other.

	--also, need to know, when calling a library, whether it's
	thread-safe: printf, malloc, etc. If not, surround call with
	mutex. (Can always surround calls with mutexes conservatively.)

        --basically locks bubble out of the interface

    What's the fundamental problem? The fundamental problem is that the
    shared memory programming model is hard to use correctly (although
    mutexes help a great deal). 

6. Mutexes and interleavings 

    Recap the environment:

        --sequential consistency means arbitrary interleavings in
        program order: this is hard enough, but ...
        
        --... modern multi-CPU hardware doesn't give sequential
        consistency, so the possible interleavings are even worse.
        
        [see end of handout07 and also panel 4 on handout03.]

    YET!!! if you use mutexes correctly

        (i) you don't have to worry about arbitrary interleavings
        (critical sections execute atomically, and interleavings in
        non-critical sections are okay), and 

        (ii) your program will appear to be running on sequentially
        consistent hardware (even if it isn't). That is, IF you use
        mutexes correctly, you don't have to worry about what the
        hardware is truly doing. 

            --> this is arranged by the threading library
            (synchronization primitives) and the compiler.

            --> in the spinlock implementation that we studied, the
            "xchg" does a lot of the required work.
       
    BUT! If you are writing low-level code (or *implementing* a
    synchronization primitive), then:

        --you MUST ensure that the compiler is not reordering key
        instructions.

        --you MUST know the memory model (of the hardware)

        --you MAY need to compensate for it, by inserting memory
        barriers (see below).
      
        (moral of the story: if you're writing systems software, you
        need to "read the manual", for both compiler and hardware.)

    What's a memory barrier?

        --instruction like MFENCE on the x86. example:

             move $1, 0x10000   # write 1 to memory address 10000
             move $2, 0x20000   # write 2 to memory address 20000
             MFENCE
             move $3, 0x10000   # write 3 to memory address 10000
             move $4, 0x30000   # write 4 to memory address 30000

        --the MFENCE here ensures that 
            
            the first two store instructions will both appear to other
            CPUs to be happening before the last two (though the first
            two may appear out of order to other CPUs, and likewise the
            last two).
       
            a more technical way to put it is: The MFENCE ensures
            that, if any memory write after the MFENCE (in program
            order) is visible to another CPU, then that other CPU
            also sees all memory writes before the MFENCE.
            

        --the "acquire" and "release" in mutexes need memory barriers.
        This ensures that from the perspective of the other CPUs, all
        memory accesses in the critical section happened AFTER acquiring
        the lock and BEFORE releasing it.
        
            Exercise: convince yourself that a memory barrier in
            acquire() and release() indeed has this effect, and that,
            without the memory barrier, the effect is not in place.

        --NOTE: on the x86, the "xchg" instruction includes an
        implicit memory barrier. This is the reason that we use
        xchg in the release() function of the spinlock
        If we implemented release() as 
            locked = 0,
        then this operation could be reordered with respect to the
        critical section, thereby violating mutual exclusion.


[thanks to David Mazières and Mike Dahlin for content in portions of
this lecture]