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Speculative Parallelization in Decoupled Look-ahead

Speculative Parallelization in Decoupled Look-ahead. Alok Garg , Raj Parihar , and Michael C. Huang Dept. of Electrical & Computer Engineering University of Rochester, Rochester, NY. Motivation. Single-thread performance still important design goal

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Speculative Parallelization in Decoupled Look-ahead

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  1. Speculative Parallelization in Decoupled Look-ahead AlokGarg, Raj Parihar, and Michael C. Huang Dept. of Electrical & Computer Engineering University of Rochester, Rochester, NY

  2. Motivation • Single-thread performance still important design goal • Branch mispredictions and cache misses are still important performance hurdles • One effective approach: Decoupled Look-ahead • Look-ahead thread can often become the new bottleneck • Speculative parallelization aptly suited for its acceleration • More parallelism opportunities: Look-ahead thread does not contain all dependences • Simple architectural support: Look-ahead not correctness critical

  3. Outline • Motivation • Baseline decoupled look-ahead • Speculative parallelization in look-ahead • Experimental analysis • Summary

  4. Baseline Decoupled Look-ahead • Binary parser is used to generate skeleton from original program • The skeleton runs on a separate core and • Maintains its own memory image in local L1, no write-back to shared L2 • Sends all branch outcomes through FIFO queue and also helps prefetching *A. Garg and M. Huang. “A Performance-Correctness Explicitly Decoupled Architecture”. In Proc. Int’l Symp. On Microarch., November 2008

  5. Practical Advantages of Decoupled Look-ahead • Look-ahead thread is a single, self-reliant agent • No need for quick spawning and register communication support • Little management overhead on main thread • Easier for run-time control to disable • Natural throttling mechanism to prevent run-away prefetching • Look-ahead thread size comparable to aggregation of short helper threads

  6. Look-ahead: A New Bottleneck • Comparing four systems • Baseline • Decoupled look-ahead • Ideal • Look-ahead alone • Application categories • Bottlenecks removed • Speed of look-ahead not the problem • Look-ahead is the new bottleneck

  7. Outline • Motivation • Baseline decoupled look-ahead • Speculative parallelization in look-ahead • Experimental analysis • Summary

  8. Unique Opportunities • Skeleton code offers more parallelism • Certain dependencies removed during slicing for skeleton • Look-ahead is inherently error-tolerant • Can ignore dependence violations • Little to no support needed, unlike in conventional TLS Assembly code from equake

  9. Software Support Parallelism at basic block level • Dependence analysis • Profile guided, coarse-grain at basic block level • Spawn and Target points • Basic blocks with consistent dependence distance of more than threshold of DMIN • Spawned thread executes from target point • Loop level parallelism is also exploited Spawn Target Time Available parallelism for 2 core/contexts system

  10. Parallelism in Look-ahead Binary Available theoretical parallelism for 2 core/contexts system; DMIN = 15 BB Parallelism potential with stables and consistent target and spawn points

  11. Hardware and Runtime Support • Thread spawning and merging • Not too different from regular thread spawning except • Spawned thread shares the same register and memory state • Spawning thread will terminate at the target PC • Value communication • Register-based naturally through shared registers in SMT • Memory-based communication can be supported at different levels • Partial versioning in cache at line level Spawning of a new look-ahead thread

  12. Outline • Motivation • Baseline decoupled look-ahead • Speculative parallelization in look-ahead • Experimental analysis • Summary

  13. Experimental Setup • Program/binary analysis tool: based on ALTO • Simulator: based on heavily modified SimpleScalar • SMT, look-ahead and speculative parallelization support • True execution-driven simulation (faithfully value modeling) Microarchitectural and cache configurations

  14. Speedup of speculative parallel decoupled look-ahead • 14 applications in which look-ahead is bottleneck • Speedup of look-ahead systems over single thread • Decoupled look-ahead over single thread baseline: 1.61x • Speculative look-ahead over single thread baseline: 1.81x • Speculative look-ahead over decoupled look-ahead:1.13x

  15. Speculative Parallelization in Look-ahead vs Main thread • Skeleton provides more opportunities for parallelization • Speedup of speculative parallelization • Speculative look-ahead over decoupled LA baseline: 1.13x • Speculative main thread over single thread baseline: 1.07x IPC 1.81x Baseline (ST) 1.07x Baseline TLS Decoupled LA 1.13x LA Speculative LA LA1 LA0 Core2 Core1

  16. Flexibility in Hardware Design • Comparison of regular (partial versioning) cache support with two other alternatives • No cache versioning support • Dependence violation detection and squash

  17. Other Details in the Paper • The effect of spawning look-ahead thread in preserving the leadof overall look-ahead system • Technique to avoid spurious spawns in dispatch stage which could be subjected to branch misprediction • Technique to mitigate the damage of runaway spawns • Impact of speculative parallelization on overall recoveries • Modifications to branch queue in multiple look-ahead system

  18. Outline • Motivation • Baseline decoupled look-ahead • Speculative parallelization in look-ahead • Experimental analysis • Summary

  19. Summary • Decoupled look-ahead can significantly improve single-thread performance but look-ahead thread often becomes new bottleneck • Look-ahead thread lends itself to TLS acceleration • Skeleton construction removes dependences and increases parallelism • Hardware design is flexible and can be a simple extension of SMT • A straightforward implementation of TLS look-ahead achieves an average 1.13x (up to 1.39x) speedup

  20. Backup Slides Speculative Parallelization in Decoupled Look-ahead AlokGarg, Raj Parihar, and Michael C. Huang Dept. of Electrical & Computer Engineering University of Rochester, Rochester, NY http://www.ece.rochester.edu/projects/acal/

  21. References (Partial) • J. Dundas and T. Mudge. Improving Data Cache Performance by Pre-Executing Instructions Under a Cache Miss. In Proc. Int’l Conf. on Supercomputing, pages 68–75, July 1997. • O. Mutlu, J. Stark, C. Wilkerson, and Y. Patt. Runahead Execution: An Alternative to Very Large Instruction Windows for Out-of-order Processors. In Proc. Int’l Symp. on High-Perf. Comp. Arch., pages 129–140, February 2003. • J. Collins, H. Wang, D. Tullsen, C. Hughes, Y. Lee, D. Lavery, and J. Shen. Speculative Precomputation: Long-range Prefetching of Delinquent Loads. In Proc. Int’l Symp. On Comp. Arch., pages 14–25, June 2001. • C. Zilles and G. Sohi. Execution-Based Prediction Using Speculative Slices. In Proc. Int’l Symp. on Comp. Arch., pages 2–13, June 2001. • A. Roth and G. Sohi. Speculative Data-Driven Multithreading. In Proc. Int’l Symp. on High-Perf. Comp. Arch., pages 37–48, January 2001. • Z. Purser, K. Sundaramoorthy, and E. Rotenberg. A Study of Slipstream Processors. In Proc. Int’l Symp. on Microarch., pages 269–280, December 2000. • G. Sohi, S. Breach, and T. Vijaykumar. Multiscalar Processors. In Proc. Int’l Symp. on Comp. Arch., pages 414–425, June 1995.

  22. References (cont…) • H. Zhou. Dual-Core Execution: Building a Highly Scalable Single-Thread Instruction Window. In Proc. Int’l Conf. on Parallel Arch. and Compilation Techniques, pages 231–242, September 2005. • A. Garg and M. Huang. A Performance-Correctness Explicitly Decoupled Architecture. In Proc. Int’l Symp. On Microarch., November 2008. • C. Zilles and G. Sohi. Master/Slave Speculative Parallelization. In Proc. Int’l Symp. on Microarch., pages 85–96, Nov 2002. • D. Burger and T. Austin. The SimpleScalar Tool Set, Version 2.0. Technical report 1342, Computer Sciences Department, University of Wisconsin-Madison, June 1997. • J. Renau, K. Strauss, L. Ceze,W. Liu, S. Sarangi, J. Tuck, and J. Torrellas. Energy-Efficient Thread-Level Speculation on a CMP. IEEE Micro, 26(1):80–91, January/February 2006. • P. Xekalakis, N. Ioannou, and M. Cintra. Combining Thread Level Speculation, Helper Threads, and Runahead Execution. In Proc. Intl. Conf. on Supercomputing, pages 410–420, June 2009. • M. Cintra, J. Martinez, and J. Torrellas. Architectural Support for Scalable Speculative Parallelization in Shared-Memory Multiprocessors. In Proc. Int’l Symp. on Comp. Arch., pages 13–24, June 2000.

  23. Backup Slides For reference only

  24. Register Renaming Support

  25. Modified Banked Branch Queue

  26. Speedup of all applications

  27. Impact on Overall Recoveries

  28. “Partial” Recovery in Look-ahead • When recovery happens in primary look-ahead • Do we kill the secondary look-ahead or not? • If we don’t kill we gain around 1% performance improvement • After recovery in main, secondary thread survives often (1000 insts) • Spawning of a secondary look-ahead thread helps preserving the slip of overall look-ahead system

  29. Quality of Thread Spawning • Successful and run-away spawns: killed after certain time • Impact of lazyspawning policy • Wait for few cycles when spawning opportunity arrives • Avoids spurious spawns; Saves some wrong path execution

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