Lecture 6 1 Concurrent Data Structures Concurrent Linked
- Slides: 137
Lecture 6 -1 : Concurrent Data Structures (Concurrent Linked Lists) Companion slides for The Art of Multiprocessor Programming by Maurice Herlihy & Nir Shavit
Concurrent Data Structures • We assume – shared-memory multiprocessors environment – concurrently execute multiple threads which communicate and synchronize through data structures in shared memory Art of Multiprocessor Programming 2
Concurrent Data Structures • Far more difficult to design than sequential ones – Correctness • Primary source of difficulty is concurrency • The steps of different threads can be interleaved arbitrarily – Scalability (performance) • We will look at – Concurrent Linked List/Queue/Stack Art of Multiprocessor Programming 3
Main performance issue of lock based system • Sequential bottleneck – At any point in time, at most one lock-protected operation is doing useful work. • Memory contention – Overhead in traffic as a result of multiple threads concurrently attempting to access the same memory location. • Blocking – If thread that currently holds the lock is delayed, then all other threads attempting to access are also delayed. – Consider non-blocking (lock-free) algorithm 4
Nonblocking algorithms • implemented by a hardware operation – atomically combines a load and a store – Ex) compare-and-swap(CAS) • lock-free – if there is guaranteed system-wide progress; – while a given thread might be blocked by other threads, all CPUs can continue doing other useful work without stalls. • wait-free – if there is also guaranteed per-thread progress. – in addition to all CPUs continuing to do useful work, no computation can ever be blocked by another 5 computation.
Linked List • Illustrate these patterns … • Using a list-based Set – Common application – Building block for other apps Art of Multiprocessor Programming 6
Set Interface • Unordered collection of items • No duplicates • Methods – add(x) put x in set – remove(x) take x out of set – contains(x) tests if x in set Art of Multiprocessor Programming 7
List-Based Sets public interface Set<T> { public boolean add(T x); public boolean remove(T x); public boolean contains(T x); } Art of Multiprocessor Programming 8
List Node public class Node { public T item; // item of interest public int key; // usually hash code public Node next; // reference to next node } Art of Multiprocessor Programming 9
The List-Based Set -∞ a b c +∞ Sorted with Sentinel nodes (min & max possible keys) Art of Multiprocessor Programming 10
Sequential List Based Set Add() a c d a b c Remove() Art of Multiprocessor Programming 11
Sequential List Based Set Add() a c d b c b Remove() a Art of Multiprocessor Programming 12
Course Grained Locking a b Art of Multiprocessor Programming d 13
Course Grained Locking a d b c Art of Multiprocessor Programming 14
Course Grained Locking a d b honk! c Simple but hotspot + bottleneck Art of Multiprocessor Programming 15
Coarse-Grained Synchronization • Sequential bottleneck – Threads “stand in line” • Adding more threads – Does not improve throughput – Struggle to keep it from getting worse • So why even use a multiprocessor? – Well, some apps inherently parallel … Art of Multiprocessor Programming 16
Coarse-Grained Synchronization (Linked List) public class private Node private Lock Coarse. List<T> { head; tail; lock = new Reentrant. Lock(); public Coarse. List() { // Add sentinels to start and end head = new Node(Integer. MIN_VALUE); tail = new Node(Integer. MAX_VALUE); head. next = this. tail; } public boolean add(T item) { Node pred, curr; int key = item. hash. Code(); lock(); try { pred = head; curr = pred. next; while (curr. key < key) { pred = curr; curr = curr. next; } if (key == curr. key) { return false; } else { Node node = new Node(item); node. next = curr; pred. next = node; return true; } } finally { lock. unlock(); } 17 }
public boolean remove(T item) { Node pred, curr; int key = item. hash. Code(); lock(); try { pred = this. head; curr = pred. next; while (curr. key < key) { pred = curr; curr = curr. next; } if (key == curr. key) pred. next = curr. next; return true; } else { return false; } } finally { lock. unlock(); } } public boolean contains(T item) { Node pred, curr; int key = item. hash. Code(); lock(); try { pred = head; curr = pred. next; while (curr. key < key) { pred = curr; curr = curr. next; } return (key == curr. key); } finally { lock. unlock(); } } 18
Coarse-Grained Locking • Easy, same as synchronized methods – “One lock to rule them all …” • Simple, clearly correct – Deserves respect! • Works poorly with contention Art of Multiprocessor Programming 19
Performance Improvement • For highly-concurrent objects • Goal: – Concurrent access – More threads, more throughput Art of Multiprocessor Programming 20
First: Fine-Grained Synchronization • Instead of using a single lock. . • Split object into – Independently-synchronized components • Methods conflict when they access – The same component … – At the same time Art of Multiprocessor Programming 21
Second: Optimistic Synchronization • Search without locking … • If you find it, lock and check … – OK: we are done – Oops: start over • Evaluation – Usually cheaper than locking – Mistakes are expensive Art of Multiprocessor Programming 22
Third: Lazy Synchronization • Postpone hard work • Removing components is tricky – Logical removal • Mark component to be deleted – Physical removal • Do what needs to be done Art of Multiprocessor Programming 23
Fourth: Lock-Free Synchronization • Don’t use locks at all – Use compare. And. Set() & relatives … • Advantages – No Scheduler Assumptions/Support • Disadvantages – Complex – Sometimes high overhead Art of Multiprocessor Programming 24
Fine-grained Locking • Requires careful thought – “Do not meddle in the affairs of wizards, for they are subtle and quick to anger” • Split object into pieces – Each piece has own lock – Methods that work on disjoint pieces need not exclude each other Art of Multiprocessor Programming 25
Fine-grained Locking • Use multiple locks of small granularity to protect different parts of the data structure • Goal – To allow concurrent operations to proceed in parallel when they do not access the same parts of the data structure Art of Multiprocessor Programming 26
Hand-over-Hand locking a b Art of Multiprocessor Programming c 27
Hand-over-Hand locking a b Art of Multiprocessor Programming c 28
Hand-over-Hand locking a b Art of Multiprocessor Programming c 29
Hand-over-Hand locking a b Art of Multiprocessor Programming c 30
Hand-over-Hand locking a b Art of Multiprocessor Programming c 31
Removing a Node a b c d remove(b) Art of Multiprocessor Programming 32
Removing a Node a b c d remove(b) Art of Multiprocessor Programming 33
Removing a Node a b c d remove(b) Art of Multiprocessor Programming 34
Removing a Node a b c d remove(b) Art of Multiprocessor Programming 35
Removing a Node a b c d remove(b) Art of Multiprocessor Programming 36
Removing a Node a remove(b) c d Why do we need to always hold 2 locks? Art of Multiprocessor Programming 37
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 38
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 39
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 40
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 41
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 42
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 43
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 44
Concurrent Removes a b c d remove(c) remove(b) Art of Multiprocessor Programming 45
Uh, Oh a c d remove(c) remove(b) Art of Multiprocessor Programming 46
Uh, Oh Bad news, C not removed a c d remove(c) remove(b) Art of Multiprocessor Programming 47
Problem • To delete node c – Swing node b’s next field to d a b c • Problem is, – Someone deleting b concurrently could direct a pointer a b c to c Art of Multiprocessor Programming 48
Insight • If a node is locked – No one can delete node’s successor • If a thread locks – Node to be deleted – And its predecessor – Then it works Art of Multiprocessor Programming 49
Hand-Over-Hand Again a b c d remove(b) Art of Multiprocessor Programming 50
Hand-Over-Hand Again a b c d remove(b) Art of Multiprocessor Programming 51
Hand-Over-Hand Again a b c d remove(b) Art of Multiprocessor Programming 52
Hand-Over-Hand Again a b c d Found it! remove(b) Art of Multiprocessor Programming 53
Hand-Over-Hand Again a b c d Found it! remove(b) Art of Multiprocessor Programming 54
Hand-Over-Hand Again a c d remove(b) Art of Multiprocessor Programming 55
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 56
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 57
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 58
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 59
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 60
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 61
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 62
Removing a Node a b c d remove(c) remove(b) Art of Multiprocessor Programming 63
Removing a Node a b c d remove(c) Must acquire Lock of b Art of Multiprocessor Programming 64
Removing a Node a b c d remove(c) Cannot acquire lock of b Art of Multiprocessor Programming 65
Removing a Node a b c d remove(c) Wait! Art of Multiprocessor Programming 66
Removing a Node a b d Proceed to remove(b) Art of Multiprocessor Programming 67
Removing a Node a b d remove(b) Art of Multiprocessor Programming 68
Removing a Node a b d remove(b) Art of Multiprocessor Programming 69
Removing a Node a d remove(b) Art of Multiprocessor Programming 70
Removing a Node a d Art of Multiprocessor Programming 71
public boolean add(T item) { int key = item. hash. Code(); head. lock(); Node pred = head; try { Node curr = pred. next; curr. lock(); try { while (curr. key < key) { pred. unlock(); pred = curr; curr = curr. next; curr. lock(); } if (curr. key == key) return false; Node new. Node = new Node(item); new. Node. next = curr; pred. next = new. Node; return true; } finally { curr. unlock(); } } finally { pred. unlock(); } } Fine-Grained Synchronization: hand-over-hand locking Linked List 72
public boolean remove(T item) { Node pred = null, curr = null; int key = item. hash. Code(); head. lock(); try { pred = head; curr = pred. next; curr. lock(); try { while (curr. key < key) { pred. unlock(); pred = curr; curr = curr. next; curr. lock(); } if (curr. key == key) { pred. next = curr. next; return true; } return false; } finally { curr. unlock(); } } finally { pred. unlock(); } } public boolean contains(T item) { Node last = null, pred = null, curr = null; int key = item. hash. Code(); head. lock(); try { pred = head; curr = pred. next; curr. lock(); try { while (curr. key < key) { pred. unlock(); pred = curr; curr = curr. next; curr. lock(); } return (curr. key == key); } finally { curr. unlock(); } } finally { pred. unlock(); } } 73 }
Adding Nodes • To add node e – Must lock predecessor – Must lock successor • Neither can be deleted – (Is successor lock actually required? ) Art of Multiprocessor Programming 75
Drawbacks • Better than coarse-grained lock – Threads can traverse in parallel • Still not ideal – Long chain of acquire/release – Inefficient Art of Multiprocessor Programming 76
Optimistic Synchronization • Find nodes without locking • Lock nodes • Check that everything is OK Art of Multiprocessor Programming 77
Optimistic: Traverse without Locking a add(c) b e d Aha! Art of Multiprocessor Programming 78
Optimistic: Lock and Load a b e d add(c) Art of Multiprocessor Programming 79
What could go wrong? a add(c) b e d Aha! Art of Multiprocessor Programming remove(b ) 80
Validate – Part 1 (while holding locks) a add(c) b e d Yes, b still reachable from head Art of Multiprocessor Programming 81
What Else Can Go Wrong? a b e d add(c) Art of Multiprocessor Programming 82
What Else Can Go Wrong? b’ a b e d add(b’) add(c) Art of Multiprocessor Programming 83
What Else Can Go Wrong? b’ a add(c) b e d Aha! Art of Multiprocessor Programming 84
Validate Part 2 (while holding locks) a add(c) b e d Yes, b still points to d Art of Multiprocessor Programming 85
Optimistic: Linearization Point a b e d c add(c) Art of Multiprocessor Programming 86
Correctness • If – Nodes b and c both locked – Node b still accessible – Node c still successor to b • Then – Neither will be deleted – OK to delete and return true Art of Multiprocessor Programming 87
Unsuccessful Remove a b d e Aha! remove(c) Art of Multiprocessor Programming 88
Validate (1) a remove(c) b d e Yes, b still reachable from head Art of Multiprocessor Programming 89
Validate (2) a remove(c) b d e Yes, b still points to d Art of Multiprocessor Programming 90
OK Computer a remove(c) b d e return false Art of Multiprocessor Programming 91
Correctness • If – Nodes b and d both locked – Node b still accessible – Node d still successor to b • Then – Neither will be deleted – No thread can add c after b – OK to return false Art of Multiprocessor Programming 92
Validation private boolean validate(Node pred, Node curry) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } return false; } Art of Multiprocessor Programming 93
Validation private boolean validate(Node pred, Node curr) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } Predecessor & return false; current nodes } Art of Multiprocessor Programming 94
Validation private boolean validate(Node pred, Node curr) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } Begin at the return false; } beginning Art of Multiprocessor Programming 95
Validation private boolean validate(Node pred, Node curr) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } Search range of keys return false; } Art of Multiprocessor Programming 96
Validation private boolean validate(Node pred, Node curr) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } return false; Predecessor reachable } Art of Multiprocessor Programming 97
Validation private boolean validate(Node pred, Node curry) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } return false; Is current node next? } Art of Multiprocessor Programming 98
Validation private boolean Otherwise move on validate(Node pred, Node curr) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } return false; } Art of Multiprocessor Programming 99
Validation private boolean Predecessor not reachable validate(Node pred, Node curr) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; node = node. next; } return false; } Art of Multiprocessor Programming 100
public boolean add(T item) { int key = item. hash. Code(); while (true) { Node pred = this. head; Node curr = pred. next; while (curr. key < key) { pred = curr; curr = curr. next; } pred. lock(); curr. lock(); try { if (validate(pred, curr)) { if (curr. key == key) { return false; } else { Node node = new Entry(item); entry. next = curr; pred. next = node; return true; } } } finally { pred. unlock(); curr. unlock(); } } } Optimistic Synchronization 101
public boolean remove(T item) { int key = item. hash. Code(); while (true) { Node pred = this. head; Node curr = pred. next; while (curr. key < key) { pred = curr; curr = curr. next; } pred. lock(); curr. lock(); try { if (validate(pred, curr)) { if (curr. key == key) { pred. next = curr. next; return true; } else { return false; } } } finally { pred. unlock(); curr. unlock(); } } } public boolean contains(T item) { int key = item. hash. Code(); while (true) { Node pred = this. head; Node curr = pred. next; while (curr. key < key) { pred = curr; curr = curr. next; } try { pred. lock(); curr. lock(); if (validate(pred, curr)) { return (curr. key == key); } } finally { pred. unlock(); curr. unlock(); } } } private boolean validate(Node pred, Node curr) { Node node = head; while (node. key <= pred. key) { if (node == pred) return pred. next == curr; Node = node. next; } return false; 102 }
Optimistic List • Limited hot-spots – Targets of add(), remove(), contains() – No contention on traversals • Moreover – Traversals are wait-free – Food for thought … Art of Multiprocessor Programming 103
So Far, So Good • Much less lock acquisition/release – Performance – Concurrency • Problems – Need to traverse list twice – contains() method acquires locks Art of Multiprocessor Programming 104
Evaluation • Optimistic is effective if – cost of scanning twice without locks is less than – cost of scanning once with locks • Drawback – contains() acquires locks – 90% of calls in many apps Art of Multiprocessor Programming 105
Lazy List • Like optimistic, except – Scan once – contains(x) never locks … • Key insight – Removing nodes causes trouble – Do it “lazily” Art of Multiprocessor Programming 106
Lazy List • remove() – Scans list (as before) – Locks predecessor & current (as before) • Logical delete – Marks current node as removed (new!) • Physical delete – Redirects predecessor’s next (as before) Art of Multiprocessor Programming 107
Lazy Removal a b d c Art of Multiprocessor Programming 108
Lazy Removal a b d c Present in list Art of Multiprocessor Programming 109
Lazy Removal a b d c Logically deleted Art of Multiprocessor Programming 110
Lazy Removal a b d c Physically deleted Art of Multiprocessor Programming 111
Lazy Removal a d b Physically deleted Art of Multiprocessor Programming 112
Lazy List • All Methods – Scan through locked and marked nodes – Removing a node doesn’t slow down other method calls … • Must still lock pred and curr nodes. Art of Multiprocessor Programming 113
Validation • • No need to rescan list! Check that pred is not marked Check that curr is not marked Check that pred points to curr Art of Multiprocessor Programming 114
Business as Usual a b c Art of Multiprocessor Programming 115
Business as Usual a b c Art of Multiprocessor Programming 116
Business as Usual a b c Art of Multiprocessor Programming 117
Business as Usual a b c remove(b) Art of Multiprocessor Programming 118
Business as Usual a b c a not marked Art of Multiprocessor Programming 119
Business as Usual a b c a still points to b Art of Multiprocessor Programming 120
Business as Usual a b c Logical delete Art of Multiprocessor Programming 121
Business as Usual a b c physical delete Art of Multiprocessor Programming 122
Business as Usual a b c Art of Multiprocessor Programming 123
Invariant • If not marked then item in the set • and reachable from head • and if not yet traversed it is reachable from pred Art of Multiprocessor Programming 124
Validation private boolean validate(Node pred, Node curr) { return !pred. marked && !curr. marked && pred. next == curr); } Art of Multiprocessor Programming 125
List Validate Method private boolean validate(Node pred, Node curr) { return !pred. marked && !curr. marked && pred. next == curr); } Predecessor not Logically removed Art of Multiprocessor Programming 126
List Validate Method private boolean validate(Node pred, Node curr) { return !pred. marked && !curr. marked && pred. next == curr); } Current not Logically removed Art of Multiprocessor Programming 127
List Validate Method private boolean validate(Node pred, Node curr) { return !pred. marked && !curr. marked && pred. next == curr); } Predecessor still Points to current Art of Multiprocessor Programming 128
Contains public boolean contains(Item item) { int key = item. hash. Code(); Node curr = this. head; while (curr. key < key) { curr = curr. next; } return curr. key == key && !curr. marked; } Art of Multiprocessor Programming 129
Contains public boolean contains(Item item) { int key = item. hash. Code(); Node curr = this. head; while (curr. key < key) { curr = curr. next; } return curr. key == key && !curr. marked; } Start at the head Art of Multiprocessor Programming 130
Contains public boolean contains(Item item) { int key = item. hash. Code(); Node curr = this. head; while (curr. key < key) { curr = curr. next; } return curr. key == key && !curr. marked; } Search key range Art of Multiprocessor Programming 131
Contains public boolean contains(Item item) { int key = item. hash. Code(); Node curr = this. head; while (curr. key < key) { curr = curr. next; } return curr. key == key && !curr. marked; } Traverse without locking (nodes may have been removed) Art of Multiprocessor Programming 132
Contains public boolean contains(Item item) { int key = item. hash. Code(); Node curr = this. head; while (curr. key < key) { curr = curr. next; } return curr. key == key && !curr. marked; } Present and undeleted? Art of Multiprocessor Programming 133
public boolean add(T item) { int key = item. hash. Code(); while (true) { Node pred = this. head; Node curr = head. next; while (curr. key < key) { pred = curr; curr = curr. next; } pred. lock(); try { curr. lock(); try { if (validate(pred, curr)) { if (curr. key == key) { return false; } else { Node = new Node(item); Node. next = curr; pred. next = Node; return true; } } } finally { // always unlock curr. unlock(); } } finally { // always unlock pred. unlock(); } } } Lazy Synchronization 134
public boolean remove(T item) { int key = item. hash. Code(); while (true) { Node pred = this. head; Node curr = head. next; while (curr. key < key) { pred = curr; curr = curr. next; } pred. lock(); try { curr. lock(); try { if (validate(pred, curr)) { if (curr. key != key) { return false; } else { curr. marked = true; pred. next = curr. next; return true; } } } finally { curr. unlock(); } } finally { pred. unlock(); } } } public boolean contains(T item) { int key = item. hash. Code(); Node curr = this. head; while (curr. key < key) curr = curr. next; return curr. key == key && !curr. marked; } private boolean validate(Node pred, Node curr) { return !pred. marked && !curr. marked && pred. next == curr; } 135
Evaluation • Good: – contains() doesn’t lock – Good because typically high % contains() – Uncontended calls don’t re-traverse • Bad – Contended add() and remove() calls do re -traverse – Traffic jam if one thread delays Art of Multiprocessor Programming 136
Traffic Jam • Any concurrent data structure based on mutual exclusion has a weakness • If one thread – Enters critical section – And “eats the big muffin” • Cache miss, page fault, descheduled … – Everyone else using that lock is stuck! – Need to trust the scheduler…. Art of Multiprocessor Programming 137
Reminder: Lock-Free Data Structures • No matter what … – Guarantees minimal progress in any execution – i. e. Some thread will always complete a method call – Even if others halt at malicious times – Implies that implementation can’t use locks Art of Multiprocessor Programming 138
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