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Transactional Memory Lecturer: Danny Hendler
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Speeding up uni-processors is harder and harder Intel, Sun (RIP), AMD, IBM now focusing on “multi-core” architectures Already, most computers are multiprocessors How can we write correct and efficient algorithms for multiprocessors ? The Future of Computing
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A fundamental problem of thread-level parallelism. Account[i] = Account[i]-X; Account[j] = Account[j]+X;.... Account[i] = Account[i]-X; Account[j] = Account[j]+X;... Thread A Thread B But what if execution is concurrent? Must avoid race conditions
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Inter-thread synch. alternatives
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What is a transaction? A transaction is a sequence of memory reads and writes, executed by a single thread, that either commits or aborts If a transaction commits, all the reads and writes appear to have executed atomically If a transaction aborts, none of its stores take effect Transaction operations aren't visible until they commit (if they do)
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Transactions properties: A transaction satisfies the following key property: Atomicity: Each transaction either commits (its changes seem to take effect atomically) or aborts (its changes have no effect). Serializability: all committed transactions issue the same operations and receive the same responses as in some sequential history consisting only of committed transactions. Some work considers weaker or stronger requirements Isolation: Transaction writes are not visible outside the transaction until it commits
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Transactional Memory Goals A new multiprocessor architecture The goal: Implementing nonblocking synchronization that is – efficient – easy to use compared with conventional techniques based on mutual exclusion Implemented by hardware support (such as straightforward extensions to multiprocessor cache- coherence protocols) and / or by software mechanisms
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A Usage Example Locks: Lock(L[i]); Lock(L[j]); Account[i] = Account[i] – X; Account[j] = Account[j] + X; Unlock(L[j]); Unlock(L[i]); Transactional Memory: atomic { Account[i] = Account[i] – X; Account[j] = Account[j] + X; }; Account[i] = Account[i]-X; Account[j] = Account[j]+X;
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Transactions execute in commit order ld 0xdddd... st 0xbeef Transaction A Time ld 0xbeef Transaction C ld 0xbeef Re-execute with new data Commit ld 0xdddd... ld 0xbbbb Transaction B Commit Violation! 0xbeef Taken from a presentation by Royi Maimon & Merav Havuv, prepared for a seminar given by Prof. Yehuda Afek. Transactions interaction
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Software Transactional Memory for Dynamic-Sized Data Structures (DSTM – Dynamic STM) Maurice Herlihy, Victor Luchangco, Mark Moir, William N. Scherer III PODC 2003 Prepared by Adi Suissa
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Motivation Transactional Memory – simplifies parallel programming STM – Software based TM ▫ Usually simpler than Hardware based TM ▫ Can handle situations where HTM fails However: ▫ It is immature (supports static data sets and static transactions) ▫ It is complicated
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Overview Short recap and what’s new? How to use DSTM? Example Diving into DSTM Example 2 Improving performance Obstruction freedom
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Transactions Transaction – a sequence of steps executed by a single thread Transactions are atomic: each transaction either commits (it takes effect) or aborts (its effects are discarded) Transactions are linearizable: they appear to take effect in a one-at-a-time order
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The computation model Starting transaction Read-Transactional(o1) Write-Transactional(o2) Read(o3) Write(o4) Commit-Transaction
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The computation model Committing a transaction can have two outcomes: ▫ Success: the transaction’s operations take effect ▫ Failure: the operations are discarded Implemented in Java and in C++
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Previous STM designs Only static memory – need to declare the memory that can be transactioned statically ▫ We want the ability to create transactional objects dynamically Only static transactions – transactions need to declare which addresses they are going to access before the transaction begins ▫ We want to let transactions determine which object to access based on information of objects read inside a transaction and this is why it is called Dynamic Software Transactional Memory
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Overview Short recap and what’s new? How to use DSTM? Example Diving into DSTM Example 2 Improving performance Obstruction freedom
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Threads A thread that executes transactions must be inherited from TMThread Each thread can run a single transaction at a time class TMThread : Thread { void beginTransaction(); bool commitTransaction(); void abortTransaction(); } Don’t forget the run() method
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Objects (1) All transactinal objects must implement the TMCloneable interface: This method clones the object, but clone implementors don’t need to handle synchronization issues inteface TMCloneable { Object clone(); }
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Objects (2) In order to make an object transactional, need to wrap it TMObject is a container for regular Java objects Object TMObject
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Opening an object Before using a TMObject in a transaction, it must be opened An object can either be opened for READ or WRITE (and read) class TMObject { TMObject(Object obj); enum Mode {READ, WRITE}; Object open(Mode mode); }
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Overview Short recap and what’s new? How to use DSTM? Example Diving into DSTM Example 2 Improving performance Obstruction freedom
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An atomic counter (1) The counter has a single data member and two operations: The object is shared by multiple threads class Counter : TMCloneable { int counterValue = 0; void inc(); // increment the value int value(); // returns the value Object clone(); }
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An atomic counter (2) When a thread wants to access the counter in a transaction, it must first open the object using the encapsulated version: Counter counter = new Counter(); TMObject tranCounter = new TMObject(counter); ((TMThread)Thread.currentThread).beginTransaction(); … Counter counter = (Counter)tranCounter.open(WRITE); counter.inc(); … ((TMThread)Thread.currentThread).commitTransaction(); Returns true/false to indicate commit status
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Overview Short recap and what’s new? How to use DSTM? Example Diving into DSTM Example 2 Improving performance Obstruction freedom
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DSTM implementation Transactional object structure: start TMObject transaction new object old object status Data Locator
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Current object version The current object version is determined by the status of the transaction that most recently opened the object in WRITE mode: ▫ committed: the new object is the current ▫ aborted: the old object is the current ▫ active: the old object is the current, and the new is tentative The actual version only changes when a commit is successful
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Opening an object (1) Let's assume transaction A tries to open object o in WRITE mode. Let transaction B be the transaction that most recently opened o in WRITE mode. We need to distinguish between the following cases: ▫ B is committed ▫ B is aborted ▫ B is active
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Opening an object (2) – B committed start o transaction new object old object committed Data B’s Locator 1 A creates a new Locator transaction new object old object A’s Locator 2 A clones the previous new object, and sets new Data clone 3 A sets old object to the previous new active 4 Use CAS in order to replace locator If CAS fails, A restarts from the beginning
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Opening an object (3) – B aborted start o transaction new object old object aborted Data B’s Locator 1 A creates a new Locator transaction new object old object A’s Locator 2 A clones the previous old object, and sets new Data clone 3 A sets old object to the previous old active 4 Use CAS in order to replace locator
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Opening an object (4) – B active Problem: B is active and can either commit or abort, so which version (old/new) should we use? Answer: A and B are conflicting transactions, that run at the same time Use Contention Manager to decide which should continue and which should abort If B needs to abort, try to change its status to aborted (using CAS)
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Opening an object (5) Lets assume transaction A opens object o in READ mode ▫ Fetch the current version just as before ▫ Add the pair (o, v) to the readers list (read- only table)
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Committing a transaction The commit needs to do the following: 1.Validate the transaction 2.Change the transaction’s status from active to committed (using CAS)
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Validating transactions What? ▫ Validate the objects (only) read by the transaction Why? ▫ To make sure that the transaction observes a consistent state How? 1.For each pair (o, v) in the read-only table, verify that v is still the most recently committed version of o 2.Check that (status == active) If the validation fails, throw an exception so the user will restart the transaction from the beginning
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Validation inconsistency Assume two threads A and B If B after A, then o1 = 2, o2 = 1; If A after B, then o1 = 1, o2 = 2 If they run concurrently we can have o1 = 1, o2 = 1 which is illegal Thread A 1. x <- read(o1) 2. w(o2, x + 1) Thread B 1. y <- read(o2) 2. w(o1, y + 1) Initially: o1 = 0 o2 = 0
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Conflicts Conflicts are detected when: ▫ A transaction first opens an object and finds that it is open for modification by another transaction ▫ When the transaction validates its read set (on opening an object or commit)
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Overview Short recap and what’s new? How to use DSTM? Example Diving into DSTM Example 2 Improving performance Obstruction freedom
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Ordered Integer List – IntSet (1) Min348Max 6
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Ordered Integer List – IntSet (2) class List implements TMCloneable { int value; TMObject next; List(int v) { value = v; } public Object clone() { List newList = new List(value); newList.next = next; return newList; }
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Ordered Integer List – IntSet (3) class IntSet { TMObject first; // the list’s anchor IntSet() { List firstList = new List (Integer.MIN_VALUE); first = new TMObject(firstList); firstList.next = new TMObject( new List(Integer.MAX_VALUE)); }
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Ordered Integer List – IntSet (4) class IntSet { boolean insert(int v) { List newList = new List(v); TMObject newNode = new TMObject(newList); TMThread thread = Thread.currentThread(); while (true) { thread.beginTransaction(); boolean result = true; try { … } catch (Denied d) {} if (thread.commitTransaction()) return result; }
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Ordered Integer List – IntSet (5) try { List prevList = (List)this.first.open(WRITE); List currList = (List)prevList.next.open(WRITE); while (currList.value < v) { prevList = currList; currList = (List)currList.next.open(WRITE); } if (currList.value == v) { result = false; } else { result = true; newList.next = prevList.next; prevList.next = newNode; }
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Overview Short recap and what’s new? How to use DSTM? Example Diving into DSTM Example 2 Improving performance Obstruction freedom
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Single entrance What is the problem with the previous example? How can it be solved? ▫ Opening for READ on traversal ▫ Maybe something more sophisticated?
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Releasing an object An object that was open for READ can be released What does it imply? ▫ Careful planning ▫ Can increase performance ▫ What happens if we open an object, release it and open it again in the same transaction? ▫ Can lead to validation problems
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Overview Short recap and what’s new? How to use DSTM? Example Diving into DSTM Example 2 Improving performance Obstruction freedom
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Non-Blocking Algorithms A family of algorithms on a shared data Each sub-family satisfies different progress guarantees Usually, there is a correlation between the progress guarantee strength and the complexity of the algorithm
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Wait-Free algorithms An algorithm is wait-free if every operation has a bound on the number of steps it will take before completing No Starvation
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Lock-Free algorithms An algorithm is lock-free if every step taken achieves global progress Even if n-1 processes fail (while doing operations on the shared memory), the last processor can still complete its operation Example: Shavit & Touitou’s STM implementation
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Obstruction-Free algorithms An algorithm is obstruction-free if at any point, a single thread executed in isolation for a bounded number of steps will complete its operation Doesn’t avoid live-locks Example: DSTM implementation What is it good for?
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Contention Manager (CM) The contention manager arbitrates between two conflicting transactions Given two (conflicting) transactions T A, T B, then CM(T A, T B ): 1.Decides who wins 2.Decides what the loser should do (abort/wait/retry) Conflicts policy
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