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An Interim Report from the Trenches: Using STM

An Interim Report from the Trenches: Using STM. Michael L. Scott University of Rochester www.cs.rochester.edu/research/synchronization/ Microsoft Faculty Summit July 2007. RSTM. TM library for C++ Outgrowth of 3+ years experience building TM libraries for Java, C, and C++

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An Interim Report from the Trenches: Using STM

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  1. An Interim Report from the Trenches: Using STM Michael L. Scott University of Rochester www.cs.rochester.edu/research/synchronization/ Microsoft Faculty Summit July 2007

  2. RSTM • TM library for C++ • Outgrowth of 3+ years experience building TM libraries for Java, C, and C++ • “Smart pointer” API • separate “hooks” at first access (initialization) and subsequent access (dereference) • different pointer types for reading, writing, private access • checks for common mistakes • Set out to gain some experience (Dec.’06—Feb.’07)

  3. Delaunay Triangulation • Important problem incomputational geometry • Our version distinctive in mixof barriers and transactions • Highlights importance of fastprivate access (95% of time inbarrier-protected private code) • 3200 lines; 400 w/in txns • See papers on app [IISWC ’07],API experience [TRANSACT ’07],privatization [UR TR 915]; 2 BAs at PODC ‘07

  4. Lots of Annoying Problems • Simple awkwardness • accessors in C++ (Cf. C#), explicit validators, 4 pointer types, clone/redo/deactivate methods, template-based code sharing • Programming model limitations • no nontrivial constructors, destructors, non-static methods (can’t use this) • no non-local exits from transactions • explicit privatization • explicit labeling of txnal types — can’t share code • Inscrutable error messages • Compiler can fix all of these easily

  5. actively transactional • privatized • long-lived but always thread-local • thread-local and transient And Some Deeper Challenges • (without mentioning nesting, I/O, condition synch, or interoperation with legacy code) • What reverts on abort? • intuition says “everything” • library API says “what you label” • At least 4 implementation cases • Should the compiler associate these withtypes? object instances? references?How should they propagate/flow? • How much should the programmer have to know/say? • e.g. wrt privatization

  6. Conclusions • STM likely to be fast enough to use • though HW support desirable • Library-based STM • can be used for nontrivial apps • can be reasonably fast • can usefully drive runtime development • but cannot be given to naive users (“obvious” in hindsight) • Compiler support essential • for semantics, not just performance • distinguishing among sharing classes an important open problem

  7. www.cs.rochester.edu/research/synchronization/

  8. The Second ACM SIGPLANWorkshop on Transactional Computing To be held in conjunction with PODC2007 Portland, Oregon, August16,2007 Registration deadline: July 25, 2007 www.cs.rochester.edu/meetings/TRANSACT07/

  9. PPoPP'08 The 13th ACM SIGPLAN Symposium onPrinciples and Practice of Parallel Programming 20–23 February 2008 Salt Lake City, Utah (co-located with HPCA-14) Submission deadline: 13 (abstracts) / 20 Aug. 2007www.ppopp.org

  10. Concurrency Design Space Credit: Bill Scherer

  11. The Bigger Picture • Parallelism works well for • High-end scientific computing • Operating systems • Internet servers • But • Hard to find in desktop apps • Hard to write, debug, maintain, scale • TM is not a panacea; let’s be careful not to oversell it written by experts (largely) embarrassingly parallel

  12. Privatization • Allow data to move in/out of transactional world • producer/consumer, spatial partitioning, … • Conceptually simple • Two implementation problems • private code fails to see committed butnot-yet-cleaned-up updates • doomed but not-yet-aborted transaction sees private updates and takes erroneous action • Several technical solutions [URCS TR 915; PODC ’07 BA] • how to present to user?

  13. Transactional Sharing Models • Contract between the user & the system • Cf. programmer-centric memory consistency models • ideally enforced by compiler • Transactions appear to be strongly isolated if programmer follows the rules • static partition — too restrictive • partition within global consensus phases • e.g. via barriers • privatizing transactions • multiple possible implementations • strong isolation • probably too expensive for software — overkill

  14. Predicting the Future • Multicore hardware • 8-core, 32-thread processors from Sun now • dual-core processors from Intel, AMD, Sun, IBM • quad-core processors from Intel • Transactional memory • part of the HPCS projects at IBM, Cray, and Sun • commercial black box from Azul • software from Microsoft likely soon • hybrid from Sun likely soon • something from Intel likely soon • chicken-and-egg problem with workloads

  15. Where Will all the Threads Come From? • Programming idioms / design patterns • e.g., futures, dataflow, ... • Higher-level abstractions • reduce/map/scan, ... • Speculative parallelization • manual or automatic • transactions for automatic detection and recovery from uncommon data races • (Your silver bullet here)

  16. The Big Question • When will we have lots ofmultithreaded desktop applications? • server-class chips will go aggressivelymulticore soon • Sun and Azul doing it already • consumer chips will wait for applications • until that happens, get used to the performanceyou have now

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