challenges in concurrent computing

Challenges in Concurrent Computing

Danny Hendler

From the New York Times …

May 7th, 2004 – “Intel said on Friday that it was scrapping its development of a faster Pentium 4 to focus on “dual core” microprocessors, a move that is a shift in the company's business strategy….”

May 8th,2004 – “Intel … [has] decided to focus its development efforts on “dual core” processors …. with two engines instead of one, allowing for greater efficiency because the processor workload is essentially shared.”

, מצטיינים 2012למאי 20סמינר

Moore’s lawExponential growth in computing power


The Future of Computing Speeding up uni-processors is harder and harder Intel, Sun (RIP), AMD, IBM now focusing on “multi-core”

architectures Already, multiprocessors are everywhere:

o Desktops

o Laptop

o Smart phones

o Smart TVs

o ...?


How can programmers write correct, efficient and scalable algorithms for multiprocessors?


Synchronization alternatives: coarse-grained locks

Pros Easy to

program

Cons Sequential


Synchronization alternatives: fine-grained locks

Pros Potentially scalable

Cons Difficult to program

correctlyo Deadlocko Priority inversiono Convoying

Locks do not compose

compare-and-swapLoad-link/store-

conditionalSwap, fetch-and-add


Synchronization alternatives: nonblocking

synchronization Various progress guarantees

o Wait-freedom, o Lock-freedomo Obstruction-freedom

Generally requires strong synchronization

Pros Potentially scalable Avoids lock-based hazards

Cons Extremely difficult to program


Synchronization alternatives: Transactional Memory

A (memory) 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 operations take effect

Transaction operations aren't visible until they commit (if they do)

To be supported soon in hardware by Intel and IBM processors


Talk outline

IntroductionNon-blocking algorithms (separate presentation)Randomized mutual exclusion (separate presentation)

Research directions

Devising efficient implementations of transactional memory Includes incorporating OS kernel support

Devising efficient and scalable lock-based and non-blocking data structures Some find their way to Java libraries

Devising algorithms that use few barrier instructions ... , מצטיינים 2012למאי 20סמינר

Research directions: practical

Research directions: theoretical

Lower bounds and impossibility results on deterministic and randomized mutual exclusion

Lower bounds and impossibility results on concurrent data-structures' (counters, stacks, queues, ...) complexity according to various metrics.

Formulating novel realistic metrics for concurrent algorithms and corresponding upper/lower bounds


challenges in concurrent computing

Documents

concurrent algorithms

scalable algorithms

synchronization alternatives

scalable lock

talk outlineintroductionnon

transaction commits

blocking data structuressome

impossibility results