SUPPORTING LOCK-FREE COMPOSITION OF CONCURRENT DATA OBJECTS

Daniel Cederman and Philippas Tsigas

Overview

SUPPORTING OF

CONCURRENT DATA OBJECTS

COMPOSITION

LOCK-FREE

Concurrent Data Objects

Data structures shared between processes

and other …

Trees Skiplists

Queues

HashtablesFor example …

Synchronization

Synchronization is required for concurrency

Mutual exclusion Locks limits concurrency Busy waiting – repeated checks to see if

lock has been released or not Convoying – processes stack up before

locks A better approach is to use data

structuresthat are …

Overview

CONCURRENT DATA OBJECTS

COMPOSITION

LOCK-FREE

Lock-free

Lock-freedom is a progress guarantee

In practice it means that A fast process doesn’t

have to wait for a slowor dead process

Can’t be designed withblocking parts

No deadlocks

Shown to scale better than blocking approaches

DefinitionFor all possible

executions, at least one concurrent

operation will succeed in a finite number of its

own steps

Libraries using Lock-free Data Objects

Java Concurrency Package Threading Building Blocks by Intel .NET Parallel Extensions NOBLE Non-Blocking Library …

Overview

CONCURRENT DATA OBJECTS

COMPOSITION

LOCK-FREE

Composition

FC

DC

A B C

FC

DA B C

Dequeue Insert

Dequeue

Insert

Queue Tree

QueueTree

?

Challenge

Providing efficiency and correctness while dealing with Specialized designs Few common algorithmic components Complex proofs of correctness

We target a large class of concurrent data objects

Concurrent Data Objects

Have operations for insertion and removal

of elements

Can be composed to form move operations

Trees Skiplists

Queues

Hashtables

and other …

Contributions

We provide a framework that consists of three parts Properties used to identify compatible

objects Steps needed to adapt object Algorithmic design of operation for

performinglock-free moves between adapted objects

Characterization

1. Have operations equivalent to insert and remove

2. These operations are linearizable3. …4. …

Linearizability

Operation A Operation C

Operation B Operation D

Linearizable if for any concurrent history there exists a correct sequential history where …

A happens before B, if A finished before B

started

Either C happens before D

or D happens before C,if C and D are concurrent

Linearization Points

Operation A Operation C

Operation B Operation D

Linearization point

Linearization point

Linearization point

Linearization point

Linearization Points

Operation A Operation C

Operation B Operation D

Characterization

1. Have operations equivalent to insert and remove

2. These operations are linearizable3. …4. …

Insert Element into BRemove Element from A

Composition

Composition

Remove - prolog

Insert - prolog

Remove - epilog

Insert - epilog

Composition

Remove - prolog

Insert - prolog

Remove - epilog

Insert - epilog

Element to remove must be accessible here!

Characterization

1. Have operations equivalent to insert and remove

2. These operations are linearizable3. The element to remove is accessible

before the linearization point4. …

Composition

Remove - prolog

Insert - prolog

Remove - epilog

Insert - epilog

Linearization point is often a successful compare-and-swap

Composition

Remove - prolog

Insert - prolog

Remove - epilog

Insert - epilog

Prolog

Epilog

if(CAS(…))

Only fails if other process

succeeds

Failed! Failed!Success! Failed!Failed! Success!

Success! Success!

RemoveInsert DCASFailed!Failed!Failed!

Success!

Composition

Remove - prolog

Insert - prolog

Remove - epilog

Insert - epilog

Combined using a double-word

compare-and-swap

Characterization

1. Have operations equivalent to insert and remove

2. These operations are linearizable3. The element to remove is accessible

before the linearization point4. The linearization point for a successful

operation is a successful compare-and-swap

Can be composed to move operations

Compatible Concurrent Data Objects

There are a wide variety of commonly used lock-free data structures that supports these requirements Queues [PODC ‘96] Lists [PODC ‘04] Skip-Lists [IPDPS ‘03] Priority Queues [JPDC ‘05] Hash-tables [SPAA ‘02] Dictionaries [SAC ‘04] Stacks [Treiber ‘86] …

Reverts to normal compare-and-swap if used outside

move operation

Move Operation

Prolog

SCAS1

Prolog

SCAS2

Epilog

Epilog

Remove operation Insert operationMove support

Performs double-word compare-and-swap

Can only fail if other process succeeds

Case Study - Stack

bool pop(value)

while(true)

ltop = top;

if(ltop == 0) return false;

value = ltop.value;

if(cas(top, ltop, ltop.next))

return true;

Not a successful operation

Successful operation connected to a

successful CAS

Accessible before linearization point

Case Study - Stack

bool pop(value)

while(true)

ltop = top;

if(ltop == 0) return false;

value = ltop.value;

if(scas(top, ltop, ltop.next, value))

return true;

The scas is called with the value to move

Generic Move Operation

Performance Evaluation

The evaluation was performed on a machine with an Intel Core i7 950 3GHz processor and 6GB DDR3-1333 memory

4 Cores with Hyper-Threading

Enqueue Dequeue

Move

Enqueue Dequeue

Queue – Insert and Remove

1 2 4 6 8 10 12 14 160

100

200

300

400

500

600

700

Blocking

Threads

Tim

e (

ms)

Queue – Move Operations

1 2 4 6 8 10 12 14 160

500

1000

1500

2000

2500

Blocking

Threads

Tim

e (

ms)

Queue – Insert/Remove/Move

1 2 4 6 8 10 12 14 160

200

400

600

800

1000

1200

1400

1600Blocking

Threads

Tim

e (

ms)

1 2 4 6 8 10 12 14 160

50

100

150

200

250

Before After

Threads

Tim

e (

ms)

Queue – Before/After Adaptation

Summary

We provide a framework that consists of three parts Properties used to identify compatible objects Steps needed to adapt object Algorithmic design of operation for performing

lock-free moves between adapted objects

Adaptation does not affect standard operations

For more information:www.cse.chalmers.se/research/group/dcs

Thank you!