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Linux Kernel Synchronization 10/27/12 Logical Diagram Binary Memory Threads Formats Allocators Linux kernel Today’s Lecture User SynchronizationSystem Calls Kernel synchronization in the kernel RCU File System Networking Sync Don Porter CSE 506 Memory Device CPU Management Drivers Scheduler Hardware Interrupts Disk Net Consistency Why Linux Warm-up synchronization? ò What is synchronization? ò A modern OS kernel is one of the most complicated parallel programs you can study ò Code on multiple CPUs coordinate their operations ò Examples: ò Other than perhaps a database ò Includes most common synchronization patterns ò Locking provides mutual exclusion while changing a pointer-based data structure ò And a few interesting, uncommon ones ò Threads might wait at a barrier for completion of a phase of computation ò Coordinating which CPU handles an interrupt The old days: They didn’t Historical perspective worry! ò Why did OSes have to worry so much about ò Early/simple OSes (like JOS, pre-lab4): No need for synchronization back when most computers have only synchronization one CPU? ò All kernel requests wait until completion – even disk requests ò Heavily restrict when interrupts can be delivered (all traps use an interrupt gate) ò No possibility for two CPUs to touch same data 1 10/27/12 Slightly more recently A slippery slope ò Optimize kernel performance by blocking inside the kernel ò We can enable interrupts during system calls ò Example: Rather than wait on expensive disk I/O, block and ò More complexity, lower latency schedule another process until it completes ò We can block in more places that make sense ò Cost: A bit of implementation complexity ò Better CPU usage, more complexity ò Need a lock to protect against concurrent update to pages/ inodes/etc. involved in the I/O ò Could be accomplished with relatively coarse locks ò Concurrency was an optimization for really fancy OSes, ò Like the Big Kernel Lock (BKL) until… ò Benefit: Better CPU utilitzation The forcing function Performance Scalability ò Multi-processing ò How much more work can this software complete in a unit of time if I give it another CPU? ò CPUs aren’t getting faster, just smaller ò So you can put more cores on a chip ò Same: No scalability---extra CPU is wasted ò The only way software (including kernels) will get faster ò 1 -> 2 CPUs doubles the work: Perfect scalability is to do more things at the same time ò Most software isn’t scalable ò Most scalable software isn’t perfectly scalable Performance Scalability Performance Scalability (more visually intuitive) Slope =1 12 0.45 0.4 == perfect 10 0.35 scaling 8 0.3 0.25 6 Perfect Scalability Perfect Scalability 0.2 Not Scalable Not Scalable 4 Performance 0.15 Ideal: Time Somewhat scalable Somewhat scalable Execution Time (s) Execution 0.1 2 Time (s) 1 / Execution halves with 0.05 0 2x CPUS 0 1 2 3 4 1 2 3 4 CPUs CPUs 2 10/27/12 Performance Scalability Coarse vs. Fine-grained (A 3rd visual) locking 35 ò Coarse: A single lock for everything 30 ò Idea: Before I touch any shared data, grab the lock 25 ò Problem: completely unrelated operations wait on each 20 Perfect Scalability other 15 Not Scalable ò Adding CPUs doesn’t improve performance 10 Somewhat scalable 5 Execution Time (s) * CPUs Time (s) * CPUs Execution Slope = 0 0 1 == perfect2 3 4 scaling CPUs Fine-grained locking Current Reality ò Fine-grained locking: Many “little” locks for individual Fine-Grained Locking data structures ò Goal: Unrelated activities hold different locks ò Hence, adding CPUs improves performance Course-Grained ò Cost: complexity of coordinating locks Performance Locking Complexity ò Unsavory trade-off between complexity and performance scalability How do locks work? Atomic instructions ò Two key ingredients: ò A “normal” instruction can span many CPU cycles ò A hardware-provided atomic instruction ò Example: ‘a = b + c’ requires 2 loads and a store ò These loads and stores can interleave with other CPUs’ memory ò Determines who wins under contention accesses ò A waiting strategy for the loser(s) ò An atomic instruction guarantees that the entire operation is not interleaved with any other CPU ò x86: Certain instructions can have a ‘lock’ prefix ò Intuition: This CPU ‘locks’ all of memory ò Expensive! Not ever used automatically by a compiler; must be explicitly used by the programmer 3 10/27/12 Atomic instruction Atomic instructions + examples locks ò Atomic increment/decrement ( x++ or x--) ò Most lock implementations have some sort of counter ò Used for reference counting ò Say initialized to 1 ò Some variants also return the value x was set to by this ò To acquire the lock, use an atomic decrement instruction (useful if another CPU immediately changes the value) ò If you set the value to 0, you win! Go ahead ò Compare and swap ò If you get < 0, you lose. Wait L ò if (x == y) x = z; ò Atomic decrement ensures that only one CPU will decrement the value to zero ò Used for many lock-free data structures ò To release, set the value back to 1 Waiting strategies Which strategy to use? ò Spinning: Just poll the atomic counter in a busy loop; ò Main consideration: Expected time waiting for the lock when it becomes 1, try the atomic decrement again vs. time to do 2 context switches ò Blocking: Create a kernel wait queue and go to sleep, ò If the lock will be held a long time (like while waiting for yielding the CPU to more useful work disk I/O), blocking makes sense ò Winner is responsible to wake up losers (in addition to ò If the lock is only held momentarily, spinning makes sense setting lock variable to 1) ò Other, subtle considerations we will discuss later ò Create a kernel wait queue – the same thing used to wait on I/O ò Note: Moving to a wait queue takes you out of the scheduler’s run queue Linux lock types Linux spinlock (simplified) ò Blocking: mutex, semaphore 1: lock; decb slp->slock // Locked decrement of lock var jns 3f ò Non-blocking: spinlocks, seqlocks, completions // Jump if not set (result is zero) to 3 2: pause // Low power instruction, wakes on // coherence event cmpb $0,slp->slock // Read the lock value, compare to zero jle 2b // If less than or equal (to zero), goto 2 jmp 1b // Else jump to 1 and try again 3: // We win the lock 4 10/27/12 Rough C equivalent Why 2 loops? while (0 != atomic_dec(&lock->counter)) { ò Functionally, the outer loop is sufficient do { ò Problem: Attempts to write this variable invalidate it in all // Pause the CPU until some coherence other caches // traffic (a prerequisite for the counter changing) ò If many CPUs are waiting on this lock, the cache line will bounce between CPUs that are polling its value // saving power ò This is VERY expensive and slows down EVERYTHING on the system } while (lock->counter <= 0); ò The inner loop read-shares this cache line, allowing all polling in parallel } ò This pattern called a Test&Test&Set lock (vs. Test&Set) Reader/writer locks Linux RW-Spinlocks ò Simple optimization: If I am just reading, we can let ò Low 24 bits count active readers other readers access the data at the same time ò Unlocked: 0x01000000 ò To read lock: atomic_dec_unless(count, 0) ò Just no writers ò 1 reader: 0x:00ffffff ò Writers require mutual exclusion ò 2 readers: 0x00fffffe ò Etc. ò Readers limited to 2^24. That is a lot of CPUs! ò 25th bit for writer ò Write lock – CAS 0x01000000 -> 0 ò Readers will fail to acquire the lock until we add 0x1000000 Subtle issue Seqlocks ò What if we have a constant stream of readers and a ò Explicitly favor writers, potentially starve readers waiting writer? ò Idea: ò The writer will starve ò An explicit write lock (one writer at a time) ò We may want to prioritize writers over readers ò Plus a version number – each writer increments at ò For instance, when readers are polling for the write beginning and end of critical section ò How to do this? ò Readers: Check version number, read data, check again ò If version changed, try again in a loop ò If version hasn’t changed and is even, neither has data 5 10/27/12 Seqlock Example Seqlock Example 0 021 70 30 Version 8070 2030 Version Lock Lock % Time for % Time for % Time for % Time for CSE 506 All Else CSE 506 All Else What if reader Reader:! executed now? Writer:! do {! !lock();! Invariant: !v = version;! !version++;! !a = cse506;! !other = 20;! Must add up to !b = other;! !cse506 = 80;! 100% } while (v % 2 == 1 && " !version++;! ! v != version);! !unlock();! Seqlocks Composing locks ò Explicitly favor writers, potentially starve readers ò Suppose I need to touch two data structures (A and B) in the kernel, protected by two locks. ò Idea: ò What could go wrong? ò An explicit write lock (one writer at a time) ò Plus a version number – each writer increments at ò Deadlock! beginning and end of critical section ò Thread 0: lock(a); lock(b) ò Readers: Check version number, read data, check again ò Thread 1: lock(b); lock(a) ò If version changed, try again in a loop ò How to solve? ò If version hasn’t changed and is even, neither has data ò Lock ordering Lock Ordering How to order? ò A program code convention ò What if I lock each entry in a linked list.
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