Article

Compiler support for speculative multithreading architecture with probabilistic points-to analysis

Authors:

Peng-Sheng Chen,

Yuan-Shin Hwang,

Roy Dz-Ching Ju, and

Jenq Kuen LeeAuthors Info & Claims

PPoPP '03: Proceedings of the ninth ACM SIGPLAN symposium on Principles and practice of parallel programming

June 2003

Pages 25 - 36

https://doi.org/10.1145/781498.781502

Published: 11 June 2003 Publication History

Abstract

Speculative multithreading (SpMT) architecture can exploit thread-level parallelism that cannot be identified statically. Speedup can be obtained by speculatively executing threads in parallel that are extracted from a sequential program. However, performance degradation might happen if the threads are highly dependent, since a recovery mechanism will be activated when a speculative thread executes incorrectly and such a recovery action usually incurs a very high penalty. Therefore, it is essential for SpMT to quantify the degree of dependences and to turn off speculation if the degree of dependences passes certain thresholds. This paper presents a technique that quantitatively computes dependences between loop iterations and such information can be used to determine if loop iterations can be executed in parallel by speculative threads. This technique can be broken into two steps. First probabilistic points-to analysis is performed to estimate the probabilities of points-to relationships in case there are pointer references in programs, and then the degree of dependences between loop iterations is computed quantitatively. Preliminary experimental results show compiler-directed thread-level speculation based on the information gathered by this technique can achieve significant performance improvement on SpMT.

References

[1]

A. Berson, S. Smith, and K. Thearling. Building Data Mining Applications for CRM. McGraw-Hill, 1999.

Digital Library

[2]

M. Burke, P. Carini, J.-D. Choi, and M. Hind. Flow-insensitive interprocedural alias analysis in the presence of pointers. In Proceedings of the 8th International Workshop on Languages and Compilers for Parallel Computing, Columbus, Ohio, August 1995.

Digital Library

[3]

M. C. Carlisle and A. Rogers. Software caching and computation migration in olden. In Proceedings of ACM SIGPLAN Conference on Principles and Practice of Parallel Programming, pages 29--39, July 1995.

Digital Library

[4]

R.-G. Chang, T.-R. Chuang, and J. K. Lee. Efficient support of parallel sparse computation for array intrinsic functions of Fortran 90. In Conference Proceedings of the 1998 International Conference on Supercomputing, pages 45--52, Melbourne, Australia, July 13--17, 1998. ACM SIGARCH.

Digital Library

[5]

R.-G. Chang, J.-S. Li, J. K. Lee, and T.-R. Chuang. Probabilistic inference schemes for sparsity structures of fortran 90 array intrinsics. In 2001 International Conference on Parallel Processing (ICPP '01, pages 61--68, Washington - Brussels - Tokyo, Sept. 2001. IEEE.

Digital Library

[6]

J.-D. Choi, M. Burke, and P. Carini. Efficient flow-sensitive interprocedural computation of pointer-induced aliases and side effects. In Proceedings of the 20th ACM SIGPLAN-SIGACT symposium on Principles of programming languages, pages 232--245. ACM Press, 1993.

Digital Library

[7]

B. D. and T. Austin. The SimpleScalar Tool Set, Version 3.0. Unversity of Wisconsin Madison Computer Science Department.

[8]

M. Das. Unification-based pointer analysis with directional assignments. In Proceedings of the ACM SIGPLAN 2000 Conference on Programming Language Design and Implementation (PLDI-00), volume 35.5 of ACM Sigplan Notices, pages 35--46, N.Y., June ~18--21 2000. ACM Press.

[9]

A. Deutsch. Interprocedural May-Alias analysis for pointers: Beyond k-limiting. SIGPLAN Notices, 29(6):230--241, June 1994. Proceedings of the ACM SIGPLAN '94 Conference on Programming Language Design and Implementation.

Digital Library

[10]

M. Emami, R. Ghiya, and L. J. Hendren. Context-sensitive interprocedural Points-to analysis in the presence of function pointers. SIGPLAN Notices, 29(6):242--256, June 1994. Proceedings of the ACM SIGPLAN '94 Conference on Programming Language Design and Implementation.

Digital Library

[11]

L. Hammond, B. Hubbert, M. Siu, M. Prabhu, M. Chen, and K. Olukotun. The stanford hydra cmp. IEEE MICRO Magazine, March-April 2000.

Digital Library

[12]

M. S. Hecht. Flow Analysis of Computer Programs. Elsevier North-Holland, New York, 1 edition, 1977.

Digital Library

[13]

G.-H. Hwang, J. K. Lee, and R. D.-C. Ju. A function-composition approach to synthesize Fortran~90 array operations. Journal of Parallel and Distributed Computing, 54(1):1--47, 10~Oct. 1998.

Digital Library

[14]

G.-H. Hwang, J. K. Lee, and R. D.-C. Ju. Array operation synthesis to optimize HPF programs on distributed memory machines. Journal of Parallel and Distributed Computing, 61(4):467--500, Apr. 2001.

Digital Library

[15]

Y.-S. Hwang, P.-S. Chen, J. K. Lee, and R. D.-C. Ju. Probabilistic points-to analysis. In Proceedings of the 2001 International Workshop on Languages and Compilers for Parallel Computing, August 2001.

Digital Library

[16]

Intel Corporation. IA-64 Application Developer's Architecture Guide, 1999.

[17]

D.-C. R. Ju, J.-F. Collard, and K. Oukbir. Probabilistic memory disambiguation and its application to data speculation. In G. Lee and P.-C. Yew, editors, Third Workshop on Interaction between Compilers and Computer Architectures (INTERACT-3), San Jose, CA, Oct. 1998.

[18]

B. W. Kernighan and D. M. Ritchie. The C programming language, Second Edition. Prentice Hall, 1988.

Digital Library

[19]

R. Krishnaiyer, D. Kulkarni, D. M. Lavery, W. Li, C.-C. Lim, J. Ng, and D. C. Sehr. An advanced optimizer for the ia-64 architecture. IEEE Micro, 20(6):60--68, November/December 2000.

Digital Library

[20]

V. Krishnan and J. Torrellas. A chip-multiprocessor architecture with speculative multithreading. IEEE Transactions on Computers, 48(9):866--880, 1999.

Digital Library

[21]

W. Landi and B. G. Ryder. A safe approximate algorithm for interprocedural pointer aliasing. SIGPLAN Notices, 27(7):235--248, July 1992. Proceedings of the ACM SIGPLAN '92 Conference on Programming Language Design and Implementation.

Digital Library

[22]

J. K. Lee, D. Ho, and Y.-C. Chuang. Data distribution analysis and optimization for pointer based distributed programs. In Proceedings of the 1997 International Conference on Parallel Processing (ICPP '97), pages 56--63, Washington - Brussels - Tokyo, Aug. 1997. IEEE Computer Society Press.

Digital Library

[23]

Y.-J. Lin, Y.-S. Hwang, and J. K. Lee. Compiler optimizations with dsp-specific semantic descriptions. In Proceedings of the 2002 International Workshop on Languages and Compilers for Parallel Computing, July 2002.

Digital Library

[24]

S. S. Muchnick. Advanced compiler design and implementation. Morgan Kaufmann Publishers, 2929 Campus Drive, Suite 260, San Mateo, CA 94403, USA, 1997.

Digital Library

[25]

J. Oplinger, D. Heine, S.-W. Liao, B. A. Nayfeh, M. S. Lam, and K. Olukotun. Software and hardware for exploiting speculative parallelism with a multiprocessor. Technical Report CSL-TR-97-715, Stanford University, February 1997.

Digital Library

[26]

G. Ramalingam. Data flow frequency analysis. In Proceedings of the ACM SIGPLAN '96 conference on Programming language design and implementation, pages 267--277. ACM Press, 1996.

Digital Library

[27]

E. Ruf. Context-insensitive alias analysis reconsidered. SIGPLAN Notices, 30(6):13--22, June 1995. Proceedings of the ACM SIGPLAN '95 Conference on Programming Language Design and Implementation.

Digital Library

[28]

R. Rugina and M. Rinard. Pointer analysis for multithreaded programs. In Proceedings of the ACM SIGPLAN '99 conference on Programming language design and implementation, pages 77--90. ACM Press, 1999.

Digital Library

[29]

M. Shapiro and S. Horwitz. Fast and accurate flow-insensitive points-to analysis. In Conference Record of POPL '97: 24nd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pages 1--14, Paris, France, Jan. 1997.

Digital Library

[30]

M. D. Smith. The SUIF Machine Library. Division of of Engineering and Applied Science, Harvard University, March 1998.

[31]

G. S. Sohi, S. E. Breach, and T. N. Vijaykumar. Multiscalar processors. In 25 Years ISCA: Retrospectives and Reprints, pages 521--532, 1998.

Digital Library

[32]

B. Steensgaard. Points-to analysis in almost linear time. In Conference Record of POPL '96: 23nd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pages 32--41, St. Petersburg Beach, Florida, Jan. 1996.

Digital Library

[33]

B. Stroustrup. The C++ programming language. Addison-Wesley, 1991.

Digital Library

[34]

The Stanford SUIF Compiler Group. The SUIF Library. Stanford University, 1995.

[35]

J.-Y. Tsai, J. Huang, C. Amlo, D. J. Lilja, and P.-C. Yew. The superthreaded processor architecture. IEEE Transactions on Computers, 48(9):881--902, 1999.

Digital Library

[36]

J.-Y. Tsai, Z. Jiang, and P.-C. Yew. Compiler techniques for the superthreaded architectures. International Journal of Parallel Programming, 27(1):1--19, 1999.

Digital Library

[37]

T. A. Wagner, V. Maverick, S. L. Graham, and M. A. Harrison. Accurate static estimators for program optimization. In Proceedings of the ACM SIGPLAN '94 conference on Programming language design and implementation, pages 85--96. ACM Press, 1994.

Digital Library

[38]

R. P. Wilson and M. S. Lam. Efficient context-sensitive pointer analysis for c programs. In Proceedings of the conference on Programming language design and implementation, pages 1--12. ACM Press, 1995.

Digital Library

[39]

P. Wu, P. Feautrier, D. Padua, and Z. Sura. Instance-wise points-to analysis for loop-based dependence testing. In Proceedings of the 16th international conference on Supercomputing, pages 262--273. ACM Press, 2002.

Digital Library

[40]

S. H. Yong, S. Horwitz, and T. Reps. Pointer analysis for programs with structures and casting. SIGPLAN Notices, 34(5):91--103, May 1999. Proceedings of the ACM SIGPLAN '99 Conference on Programming Language Design and Implementation.

Digital Library

[41]

Y.-P. You, C.-R. Lee, and J. K. Lee. Compiler analysis and supports for leakage power reduction on microprocessors. In Proceedings of the 2002 International Workshop on Languages and Compilers for Parallel Computing, July 2002.

Digital Library

Cited By

Ying VJeffrey MSanchez D(2020)T4: Compiling Sequential Code for Effective Speculative Parallelization in Hardware2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA)10.1109/ISCA45697.2020.00024(159-172)Online publication date: May-2020
https://doi.org/10.1109/ISCA45697.2020.00024
Verbrugge CPickett CKrolik AKielstra AJannesari ASato YWinter S(2016)Exhaustive analysis of thread-level speculationProceedings of the 3rd International Workshop on Software Engineering for Parallel Systems10.1145/3002125.3002127(25-34)Online publication date: 21-Oct-2016
https://dl.acm.org/doi/10.1145/3002125.3002127
Estebanez ALlanos DGonzalez-Escribano A(2016)A Survey on Thread-Level Speculation TechniquesACM Computing Surveys10.1145/293836949:2(1-39)Online publication date: 30-Jun-2016
https://dl.acm.org/doi/10.1145/2938369
Show More Cited By

Index Terms

Compiler support for speculative multithreading architecture with probabilistic points-to analysis
1. Hardware
  1. Emerging technologies
    1. Analysis and design of emerging devices and systems
      1. Emerging languages and compilers
2. Software and its engineering
  1. Software notations and tools
    1. Compilers

Recommendations

Compiler support for speculative multithreading architecture with probabilistic points-to analysis
Proceedings of the ACM SIGPLAN symposium on principles and practice of parallel programming (PPoPP 2003) and workshop on partial evaluation and semantics-based program manipulation (PEPM 2003)

Speculative multithreading (SpMT) architecture can exploit thread-level parallelism that cannot be identified statically. Speedup can be obtained by speculatively executing threads in parallel that are extracted from a sequential program. However, ...
Read More
A thread partitioning approach for speculative multithreading

Speculative multithreading (SpMT) is a thread-level automatic parallelization technique, which partitions sequential programs into multithreads to be executed in parallel. This paper presents different thread partitioning strategies for nonloops and ...
Read More
Thread-Spawning Schemes for Speculative Multithreading
HPCA '02: Proceedings of the 8th International Symposium on High-Performance Computer Architecture

Speculative multithreading has been recently proposed to boost performance by means of exploiting thread-level parallelism in applications difficult to parallelize. The performance of these processors heavily depends on the partitioning policy used to ...
Read More

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

PPoPP '03: Proceedings of the ninth ACM SIGPLAN symposium on Principles and practice of parallel programming

June 2003

250 pages

ISBN:1581135882

DOI:10.1145/781498

General Chair:
Rudolf Eigenmann
Purdue University
,
Program Chair:
Martin Rinard
MIT Laboratory for Computer Science

ACM SIGPLAN Notices Volume 38, Issue 10
Proceedings of the ACM SIGPLAN symposium on principles and practice of parallel programming (PPoPP 2003) and workshop on partial evaluation and semantics-based program manipulation (PEPM 2003)
October 2003
331 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/966049
Issue’s Table of Contents

Copyright © 2003 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 June 2003

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

PPoPP03

Sponsor:

PPoPP03: ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

June 11 - 13, 2003

California, San Diego, USA

Acceptance Rates

PPoPP '03 Paper Acceptance Rate 20 of 45 submissions, 44%;

Overall Acceptance Rate 230 of 1,014 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

38
Total Citations
View Citations
772
Total Downloads

Downloads (Last 12 months)9
Downloads (Last 6 weeks)1

Other Metrics

View Author Metrics

Citations

Cited By

Ying VJeffrey MSanchez D(2020)T4: Compiling Sequential Code for Effective Speculative Parallelization in Hardware2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA)10.1109/ISCA45697.2020.00024(159-172)Online publication date: May-2020
https://doi.org/10.1109/ISCA45697.2020.00024
Verbrugge CPickett CKrolik AKielstra AJannesari ASato YWinter S(2016)Exhaustive analysis of thread-level speculationProceedings of the 3rd International Workshop on Software Engineering for Parallel Systems10.1145/3002125.3002127(25-34)Online publication date: 21-Oct-2016
https://dl.acm.org/doi/10.1145/3002125.3002127
Estebanez ALlanos DGonzalez-Escribano A(2016)A Survey on Thread-Level Speculation TechniquesACM Computing Surveys10.1145/293836949:2(1-39)Online publication date: 30-Jun-2016
https://dl.acm.org/doi/10.1145/2938369
Fu Z(2014)Targeted Update --- Aggressive Memory Abstraction Beyond Common Sense and Its Application on Static Numeric AnalysisProceedings of the 23rd European Symposium on Programming Languages and Systems - Volume 841010.1007/978-3-642-54833-8_28(534-553)Online publication date: 5-Apr-2014
https://dl.acm.org/doi/10.1007/978-3-642-54833-8_28
Vanka RTuck JEidt CHoller ASrinivasan UAmarasinghe S(2012)Efficient and accurate data dependence profiling using software signaturesProceedings of the Tenth International Symposium on Code Generation and Optimization10.1145/2259016.2259041(186-195)Online publication date: 31-Mar-2012
https://dl.acm.org/doi/10.1145/2259016.2259041
Samadi MHormati ALee JMahlke S(2012)ParagonProceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units10.1145/2159430.2159438(64-73)Online publication date: 3-Mar-2012
https://dl.acm.org/doi/10.1145/2159430.2159438
Hung MChen PHwang YJu RLee J(2012)Support of Probabilistic Pointer Analysis in the SSA FormIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2012.7323:12(2366-2379)Online publication date: 1-Dec-2012
https://dl.acm.org/doi/10.1109/TPDS.2012.73
Han LLiu WTuck JMoshovos ASteffan GHazelwood KKaeli D(2010)Speculative parallelization of partial reduction variablesProceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization10.1145/1772954.1772975(141-150)Online publication date: 24-Apr-2010
https://dl.acm.org/doi/10.1145/1772954.1772975
Wang XZhao YWei YSong SHan B(2010)Prophet Synchronization Thread Model and Compiler SupportProceedings of the International Symposium on Parallel and Distributed Processing with Applications10.1109/ISPA.2010.83(81-87)Online publication date: 6-Sep-2010
https://dl.acm.org/doi/10.1109/ISPA.2010.83
Das DPeng Wu (2010)Experiences of using a dependence profiler to assist parallelization for multi-cores2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)10.1109/IPDPSW.2010.5470884(1-8)Online publication date: Apr-2010
https://doi.org/10.1109/IPDPSW.2010.5470884
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents