research-article

iThreads: A Threading Library for Parallel Incremental Computation

Authors:

Pramod Bhatotia,

Björn B. Brandenburg,

Rodrigo RodriguesAuthors Info & Claims

ACM SIGPLAN Notices, Volume 50, Issue 4

Pages 645 - 659

https://doi.org/10.1145/2775054.2694371

Published: 14 March 2015 Publication History

Abstract

Incremental computation strives for efficient successive runs of applications by re-executing only those parts of the computation that are affected by a given input change instead of recomputing everything from scratch. To realize these benefits automatically, we describe iThreads, a threading library for parallel incremental computation. iThreads supports unmodified shared-memory multithreaded programs: it can be used as a replacement for pthreads by a simple exchange of dynamically linked libraries, without even recompiling the application code. To enable such an interface, we designed algorithms and an implementation to operate at the compiled binary code level by leveraging MMU-assisted memory access tracking and process-based thread isolation. Our evaluation on a multicore platform using applications from the PARSEC and Phoenix benchmarks and two case-studies shows significant performance gains.

References

[1]

PaX Team. PaX Address Space Layout Randomization (ASLR). (http://pax.grsecurity.net/docs/aslr.txt).

[2]

Monte-Carlo Method. (http://cdac.in/index.aspx?id=evhpcpthreadbenchmarkskernels).

[3]

Pigz: A parallel implementation of gzip for modern multi-processor, multi-core machines. (http://zlib.net/pigz/).

[4]

Pthreads Memory Model. (http://pubs.opengroup.org/onlinepubs/9699919799/basedefs/v1chap04.html).

[5]

M. Abadi, B. W. Lampson, and J.-J. Levy. Analysis and caching of dependencies. In proceedings of the First ACM SIGPLAN International Conference on Functional Programming (ICFP), 1996.

Digital Library

[6]

U. A. Acar. Self-Adjusting Computation. PhD thesis, Department of Computer Science, Carnegie Mellon University, May 2005.

Digital Library

[7]

U. A. Acar, G. E. Blelloch, M. Blume, R. Harper, and K. Tangwongsan. An experimental analysis of self-adjusting computation. In proceedings of the 2006 ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2009.

Digital Library

[8]

U. A. Acar, A. Cotter, B. Hudson, and D. Turkoglu. Dynamic well-spaced point sets. In proceedings of the Twenty-sixth Annual Symposium on Computational Geometry (SoCG), 2010.

Digital Library

[9]

S. V. Adve and H.-J. Boehm. Memory models: A case for rethinking parallel languages and hardware. Communication of ACM (CACM), 2010.

Digital Library

[10]

P. K. Agarwal, L. J. Guibas, H. Edelsbrunner, J. Erickson, M. Isard, S. Har-Peled, J. Hershberger, C. Jensen, L. Kavraki, P. Koehl, M. Lin, D. Manocha, D. Metaxas, B. Mirtich, D. Mount, S. Muthukrishnan, D. Pai, E. Sacks, J. Snoeyink, S. Suri, and O. Wolefson. Algorithmic issues in modeling motion. ACM Computing Survey, 2002.

Digital Library

[11]

P. S. Almeida, C. Baquero, and V. Fonte. Interval tree clocks. In proceedings of the 12th International Conference on Principles of Distributed Systems (OPODIS), 2008.

Digital Library

[12]

G. Altekar and I. Stoica. ODR: Output-deterministic Replay for Multicore Debugging. In proceedings of the ACM SIGOPS 22nd Symposium on Operating Systems Principles (SOSP), 2009.

Digital Library

[13]

A. Aviram, S.-C. Weng, S. Hu, and B. Ford. Efficient System-enforced Deterministic Parallelism. In proceedings of the9th USENIX Conference on Operating Systems Design and Implementation (OSDI), 2010.

Digital Library

[14]

T. Bergan, O. Anderson, J. Devietti, L. Ceze, and D. Grossman. CoreDet: A Compiler and Runtime System for Deterministic Multithreaded Execution. In proceedings of the fifteenth edition of Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2010.

Digital Library

[15]

T. Bergan, N. Hunt, L. Ceze, and S. D. Gribble. Deterministic Process Groups in dOS. In proceedings of the 9th USENIX conference on Operating Systems Design and Implementation (OSDI), 2010.

Digital Library

[16]

E. D. Berger, B. G. Zorn, and K. S. McKinley. Composing High-Performance Memory Allocators. In proceedings of the ACM SIGPLAN 2001 conference on Programming Language Design and Implementation (PLDI), 2001.

Digital Library

[17]

E. D. Berger, T. Yang, T. Liu, and G. Novark. Grace: Safe Multithreaded Programming for C/C++. In proceedings of the 24th ACM SIGPLAN conference on Object Oriented Programming Systems Languages and Applications (OOPSLA), 2009.

Digital Library

[18]

P. Bhatotia, A. Wieder, I. E. Akkus, R. Rodrigues, and U. A. Acar. Large-scale incremental data processing with change propagation. In USENIX Workshop on Hot Topics in Cloud Computing (HotCloud), 2011.

Digital Library

[19]

P. Bhatotia, A. Wieder, R. Rodrigues, U. A. Acar, and R. Pasquini. Incoop: MapReduce for Incremental Computations. In proceedings of the 2nd ACM Symposium on Cloud Computing (SoCC), 2011.

Digital Library

[20]

P. Bhatotia, M. Dischinger, R. Rodrigues, and U. A. Acar. Slider: Incremental Sliding-Window Computations for Large-Scale Data Analysis. In Technical Report: MPI-SWS-2012-004, 2012.

[21]

P. Bhatotia, R. Rodrigues, and A. Verma. Shredder: GPU- Accelerated Incremental Storage and Computation. In proceedings of the 10th USENIX conference on File and Storage Technologies (FAST), 2012.

Digital Library

[22]

P. Bhatotia, U. A. Acar, F. Junqueira, and R. Rodrigues. Slider: Incremental Sliding Window Analytics. In proceedings of the 15th Annual ACM/IFIP/USENIX Middleware conference (Middleware), 2014.

Digital Library

[23]

P. Bhatotia, A. Wieder, R. Rodrigues, and U. A. Acar. Incremental MapReduce Computations. In book chapter of advances in data processing techniques in the era of Big Data, CRC Press, 2014.

[24]

C. Bienia, S. Kumar, J. P. Singh, and K. Li. The PARSEC Benchmark Suite: Characterization and Architectural Implications. In proceedings of the 17th international conference on Parallel Architectures and Compilation Techniques (PACT), 2008.

Digital Library

[25]

G. S. Brodal and R. Jacob. Dynamic planar convex hull. In proceedings of the 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002.

Digital Library

[26]

Y. Bu, B. Howe, M. Balazinska, and M. D. Ernst. HaLoop: efficient iterative data processing on large clusters. In proceedings of VLDB Endowment (VLDB), 2010.

Digital Library

[27]

S. Burckhardt, D. Leijen, C. Sadowski, J. Yi, and T. Ball. Two for the Price of One: A Model for Parallel and Incremental Computation. In proceedings of the 2011 ACM international conference on Object Oriented Programming Systems Languages and Applications (OOPSLA), 2011.

Digital Library

[28]

J. B. Carter, J. K. Bennett, and W. Zwaenepoel. Implementation and Performance of Munin. In proceedings of the Thirteenth ACM Symposium on Operating Systems Principles (SOSP), 1991.

Digital Library

[29]

Y. Chen, J. Dunfield, and U. A. Acar. Type-Directed Automatic Incrementalization. In proceedings of the 33rd ACM SIGPLAN conference on Programming Language Design and Implementation (PLDI), Jun 2012.

Digital Library

[30]

Y.-J. Chiang and R. Tamassia. Dynamic algorithms in computational geometry. proceedings of the IEEE, 1992.

[31]

T. Condie, N. Conway, P. Alvaro, J. M. Hellerstein, K. Elmeleegy, and R. Sears. MapReduce online. In proceedings of the 7th USENIX Conference on Networked Systems Design and Implementation (NSDI), 2010.

Digital Library

[32]

H. Cui, J. Wu, C.-C. Tsai, and J. Yang. Stable deterministic multithreading through schedule memoization. In proceedings of the 9th USENIX Conference on Operating Systems Design and Implementation (OSDI), 2010.

Digital Library

[33]

H. Cui, J. Wu, J. Gallagher, H. Guo, and J. Yang. Efficient deterministic multithreading through schedule relaxation. In proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (SOSP), 2011.

Digital Library

[34]

H. Cui, J. Simsa, Y.-H. Lin, H. Li, B. Blum, X. Xu, J. Yang, G. A. Gibson, and R. E. Bryant. Parrot: a practical runtime for deterministic, stable, and reliable threads. In proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles (SOSP), 2013.

Digital Library

[35]

J. Dean and S. Ghemawat. MapReduce: Simplified Data Processing on Large Clusters. In proceedings of the 6th conference on Symposium on Operating Systems Design and Implementation (OSDI), 2004.

Digital Library

[36]

A. Demers, T. Reps, and T. Teitelbaum. Incremental evaluation for attribute grammars with application to syntax-directed editors. In proceedings of the 8th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL), 1981.

Digital Library

[37]

C. Demetrescu, I. Finocchi, and G. Italiano. Handbook on Data Structures and Applications, chapter 36: Dynamic Graphs. Dinesh Mehta and Sartaj Sahni (eds.), CRC Press Series, in Computer and Information Science, 2005.

[38]

C. Demetrescu, I. Finocchi, and G. Italiano. Handbook on Data Structures and Applications, chapter 35: Dynamic Trees. Dinesh Mehta and Sartaj Sahni (eds.), CRC Press Series, in Computer and Information Science, 2005.

[39]

J. Devietti, B. Lucia, L. Ceze, and M. Oskin. DMP: Deterministic Shared Memory Multiprocessing. In proceedings of the 14th international conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2009.

Digital Library

[40]

J. Devietti, J. Nelson, T. Bergan, L. Ceze, and D. Grossman. RCDC: A Relaxed Consistency Deterministic Computer. proceedings of the 16th international conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2011.

Digital Library

[41]

G. W. Dunlap, S. T. King, S. Cinar, M. A. Basrai, and P. M. Chen. ReVirt: Enabling Intrusion Analysis Through Virtual- machine Logging and Replay. proceedings of the 5th symposium on Operating Systems Design and Implementation (OSDI), 2002.

Digital Library

[42]

D. Eppstein, Z. Galil, and G. F. Italiano. Dynamic graph algorithms. In M. J. Atallah, editor, Algorithms and Theory of Computation Handbook, chapter 8. CRC Press, 1999.

[43]

C. Flanagan and S. N. Freund. FastTrack: Efficient and Precise Dynamic Race Detection. In proceedings of the 2009 ACM SIGPLAN conference on Programming Language Design and Implementation (PLDI), 2009.

Digital Library

[44]

K. Gharachorloo, D. Lenoski, J. Laudon, P. Gibbons, A. Gupta, and J. Hennessy. Memory Consistency and Event Ordering in Scalable Shared-memory Multiprocessors. In proceedings of the 17th Annual International Symposium on Computer Architecture (ISCA), 1990.

Digital Library

[45]

L. Guibas. Modeling motion. In Handbook of Discrete and Computational Geometry. 2004.

[46]

L. J. Guibas. Kinetic data structures: a state of the art report. In proceedings of the third Workshop on the Algorithmic Foundations of Robotics (WAFR), 1998.

Digital Library

[47]

P. K. Gunda, L. Ravindranath, C. A. Thekkath, Y. Yu, and L. Zhuang. Nectar: automatic management of data and computation in datacenters. In proceedings of the 9th USENIX conference on Operating systems design and implementation (OSDI), 2010.

Digital Library

[48]

M. Hammer, U. A. Acar, M. Rajagopalan, and A. Ghuloum. A proposal for parallel self-adjusting computation. In proceedings of the 2007 workshop on Declarative Aspects of Multicore Programming (DAMP), 2007.

Digital Library

[49]

M. A. Hammer, U. A. Acar, and Y. Chen. CEAL: a C-Based Language for Self-Adjusting Computation. In proceedings of the 2009 ACM SIGPLAN conference on Programming Language Design and Implementation (PLDI), 2009.

Digital Library

[50]

M. A. Hammer, K. Y. Phang, M. Hicks, and J. S. Foster. Adapton: Composable, demand-driven incremental computation. In proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2014.

Digital Library

[51]

A. Heydon, R. Levin, and Y. Yu. Caching Function Calls Using Precise Dependencies. In proceedings of the ACM SIGPLAN 2000 conference on Programming Language Design and Implementation (PLDI), 2000.

Digital Library

[52]

N. Honarmand and J. Torrellas. RelaxReplay: Record and Replay for Relaxed-consistency Multiprocessors. In proceedings of the 19th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2014.

Digital Library

[53]

R. Hoover. Incremental Graph Evaluation. PhD thesis, Department of Computer Science, Cornell University, May 1987.

Digital Library

[54]

D. R. Hower, P. Dudnik, M. D. Hill, and D. A. Wood. Calvin: Deterministic or not? free will to choose. In proceedings of the 2011 IEEE 17th International Symposium on High Performance Computer Architecture (HPCA), 2011.

Digital Library

[55]

M. Isard, M. Budiu, Y. Yu, A. Birrell, and D. Fetterly. Dryad: distributed data-parallel programs from sequential building blocks. In proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems (EuroSys), 2007.

Digital Library

[56]

P. Keleher, A. L. Cox, S. Dwarkadas, and W. Zwaenepoel. Treadmarks: Distributed shared memory on standard workstations and operating systems. In proceedings of the USENIX Winter 1994 Technical Conference on USENIX Winter 1994 Technical Conference (USENIX), 1994.

Digital Library

[57]

O. Laadan, N. Viennot, and J. Nieh. Transparent, lightweight application execution replay on commodity multiprocessor operating systems. In proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems (SIGMETRICS), 2010.

Digital Library

[58]

L. Lamport. How to make a correct multiprocess program execute correctly on a multiprocessor. IEEE Transactions on Computers, 1997.

Digital Library

[59]

D. Lee, B. Wester, K. Veeraraghavan, S. Narayanasamy, P. M. Chen, and J. Flinn. Respec: Efficient Online Multiprocessor Replay via Speculation and External Determinism. In proceedings of the 15th edition of ASPLOS on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2010.

Digital Library

[60]

R. Ley-Wild, M. Fluet, and U. A. Acar. Compiling Self-Adjusting Programs with Continuations. In proceedings of the 13th ACM SIGPLAN International Conference on Functional programming (ICFP), 2008.

Digital Library

[61]

R. Ley-Wild, U. A. Acar, and M. Fluet. A cost semantics for self-adjusting computation. In proceedings of the 26th Annual ACM Symposium on Principles of Programming Languages (POPL), 2009.

Digital Library

[62]

T. Liu and E. D. Berger. SHERIFF: Precise Detection and Automatic Mitigation of False Sharing. In proceedings of the 2011 ACM International Conference on Object Oriented Programming Systems Languages and Applications (OOPSLA), 2011.

Digital Library

[63]

T. Liu, C. Curtsinger, and E. D. Berger. Dthreads: Efficient Deterministic Multithreading. In proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (SOSP), 2011.

Digital Library

[64]

D. Logothetis, C. Olston, B. Reed, K. C. Webb, and K. Yocum. Stateful Bulk Processing for Incremental Analytics. In proceedings of the 1st ACM Symposium on Cloud Computing (SoCC), 2010.

Digital Library

[65]

F. Mattern. Virtual Time and Global States of Distributed Systems. In Parallel and Distributed Algorithms, 1989.

[66]

A. Muthitacharoen, B. Chen, and D. Mazieres. A Low-bandwidth Network File System. In proceedings of the 18th ACM Symposium on Operating Systems Principles (SOSP), 2001.

Digital Library

[67]

M. Olszewski, J. Ansel, and S. Amarasinghe. Kendo: Efficient Deterministic Multithreading in Software. In proceedings of the 14th international conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2009.

Digital Library

[68]

M. H. Overmars and J. van Leeuwen. Maintenance of configurations in the plane. Journal of Computer and System Sciences, 23:166--204, 1981.

[69]

S. Park, Y. Zhou, W. Xiong, Z. Yin, R. Kaushik, K. H. Lee, and S. Lu. PRES: Probabilistic Replay with Execution Sketching on Multiprocessors. In proceedings of the ACM SIGOPS 22nd Symposium on Operating Systems Principles (SOSP), 2009.

Digital Library

[70]

L. Popa, M. Budiu, Y. Yu, and M. Isard. DryadInc: Reusing Work in Large-scale Computations. In USENIX Workshop on Hot Topics in Cloud Computing (HotCloud), 2009.

Digital Library

[71]

E. Pozniansky and A. Schuster. Efficient On-the-Fly Data Race Detection in Multithreaded C++ Programs. In proceedings of the ninth ACM SIGPLAN symposium on Principles and Practice of Parallel Programming (PPoPP), 2003.

Digital Library

[72]

W. Pugh. Incremental Computation via Function Caching. PhD thesis, Department of Computer Science, Cornell University, Aug. 1988.

[73]

G. Ramalingam and T. Reps. A Categorized Bibliography on Incremental Computation. In proceedings of the 20th ACM SIGPLAN-SIGACT symposium on Principles of Programming Languages (POPL), 1993.

Digital Library

[74]

C. Ranger, R. Raghuraman, A. Penmetsa, G. Bradski, and C. Kozyrakis. Evaluating MapReduce for Multi-core and Multiprocessor Systems. In proceedings of the 2007 IEEE 13th International Symposium on High Performance Computer Architecture (HPCA), 2007.

Digital Library

[75]

M. Ronsse and K. De Bosschere. RecPlay: A Fully Integrated Practical Record/Replay System. ACM Transactions on Computer Systems (TOCS), 1999.

Digital Library

[76]

H.-W. Tseng and D. M. Tullsen. Data-Triggered Threads: Eliminating Redundant Computation. In proceedings of 17th International Symposium on High Performance Computer Architecture (HPCA), 2011.

Digital Library

[77]

H.-W. Tseng and D. M. Tullsen. Software Data-triggered Threads. In proceedings of the ACM International Conference on Object Oriented Programming Systems Languages and Applications (OOPSLA), 2012.

Digital Library

[78]

H.-W. Tseng and D. M. Tullsen. CDTT: Compiler-generated data-triggered threads. In proceedings of 17th International Symposium on High Performance Computer Architecture (HPCA), 2014.

[79]

K. Veeraraghavan, P. M. Chen, J. Flinn, and S. Narayanasamy. Detecting and Surviving Data Races Using Complementary Schedules. In proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (SOSP), 2011.

Digital Library

[80]

K. Veeraraghavan, D. Lee, B. Wester, J. Ouyang, P. M. Chen, J. Flinn, and S. Narayanasamy. DoublePlay: Parallelizing Sequential Logging and Replay. In proceedings of the sixteenth international conference on Architectural support for programming languages and operating system (ASPLOS), 2011.

Digital Library

[81]

N. Viennot, S. Nair, and J. Nieh. Transparent Mutable Replay for Multicore Debugging and Patch Validation. In proceedings of the 18th International Conference on Architectural Support for Programming Languages and Operating Systems(ASPLOS), 2013.

Digital Library

[82]

W. Xiong, S. Park, J. Zhang, Y. Zhou, and Z. Ma. Ad hoc Synchronization Considered Harmful. In proceedings of the 9th USENIX conference on Operating Systems Design and Implementation (OSDI), 2010.

Digital Library

Cited By

Kang P(2017)Function call interception techniquesSoftware: Practice and Experience10.1002/spe.250148:3(385-401)Online publication date: 16-May-2017
https://doi.org/10.1002/spe.2501
Wang ZPailoor SPrakash AWang YDillig I(2024)From Batch to Stream: Automatic Generation of Online AlgorithmsProceedings of the ACM on Programming Languages10.1145/36564188:PLDI(1014-1039)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3656418
Ahmad ALee SFonseca PLee BSherwood TBerger EKozyrakis C(2021)Kard: lightweight data race detection with per-thread memory protectionProceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3445814.3446727(647-660)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3445814.3446727

Index Terms

iThreads: A Threading Library for Parallel Incremental Computation

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Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 50, Issue 4

ASPLOS '15

April 2015

676 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/2775054

Editor:
Andy Gill
University of Kansas, Lawrence, KS

Issue’s Table of Contents

ASPLOS '15: Proceedings of the Twentieth International Conference on Architectural Support for Programming Languages and Operating Systems
March 2015
720 pages
ISBN:9781450328357
DOI:10.1145/2694344
General Chairs:
Ozcan Ozturk
Bilkent University, Turkey
,
Kemal Ebcioglu
Global Supercomputing, USA
,
Program Chair:
Sandhya Dwarkadas
University of Rochester, USA

Copyright © 2015 ACM.

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Publication History

Published: 14 March 2015

Published in SIGPLAN Volume 50, Issue 4

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Cited By

Kang P(2017)Function call interception techniquesSoftware: Practice and Experience10.1002/spe.250148:3(385-401)Online publication date: 16-May-2017
https://doi.org/10.1002/spe.2501
Wang ZPailoor SPrakash AWang YDillig I(2024)From Batch to Stream: Automatic Generation of Online AlgorithmsProceedings of the ACM on Programming Languages10.1145/36564188:PLDI(1014-1039)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3656418
Ahmad ALee SFonseca PLee BSherwood TBerger EKozyrakis C(2021)Kard: lightweight data race detection with per-thread memory protectionProceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3445814.3446727(647-660)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3445814.3446727
Anderson DBlelloch GBaweja AAcar UAgrawal KAzar Y(2021)Efficient Parallel Self-Adjusting ComputationProceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures10.1145/3409964.3461799(59-70)Online publication date: 6-Jul-2021
https://dl.acm.org/doi/10.1145/3409964.3461799
Bhatotia PAcar UJunqueira FRodrigues R(2019)Incremental Sliding Window AnalyticsEncyclopedia of Big Data Technologies10.1007/978-3-319-77525-8_156(1007-1015)Online publication date: 20-Feb-2019
https://doi.org/10.1007/978-3-319-77525-8_156
Quoc DChen RBhatotia PFetzer CHilt VStrufe T(2019)Approximate Computing for Stream AnalyticsEncyclopedia of Big Data Technologies10.1007/978-3-319-77525-8_153(90-97)Online publication date: 20-Feb-2019
https://doi.org/10.1007/978-3-319-77525-8_153
Quoc DBeck MBhatotia PChen RFetzer CStrufe T(2019)Privacy-Preserving Data AnalyticsEncyclopedia of Big Data Technologies10.1007/978-3-319-77525-8_152(1292-1300)Online publication date: 20-Feb-2019
https://doi.org/10.1007/978-3-319-77525-8_152
Quoc DKrishnan DBhatotia PFetzer CRodrigues R(2019)Incremental Approximate ComputingEncyclopedia of Big Data Technologies10.1007/978-3-319-77525-8_151(1000-1007)Online publication date: 20-Feb-2019
https://doi.org/10.1007/978-3-319-77525-8_151
Liu BHuang J(2018)D4: fast concurrency debugging with parallel differential analysisACM SIGPLAN Notices10.1145/3296979.319239053:4(359-373)Online publication date: 11-Jun-2018
https://dl.acm.org/doi/10.1145/3296979.3192390
Drechsler JMogk RSalvaneschi GMezini M(2018)Thread-safe reactive programmingProceedings of the ACM on Programming Languages10.1145/32764772:OOPSLA(1-30)Online publication date: 24-Oct-2018
https://dl.acm.org/doi/10.1145/3276477

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