Kendo

Kendo: efficient deterministic multithreading in software. Although chip-multiprocessors have become the industry standard, developing parallel applications that target them remains a daunting task. Non-determinism, inherent in threaded applications, causes significant challenges for parallel programmers by hindering their ability to create parallel applications with repeatable results. As a consequence, parallel applications are significantly harder to debug, test, and maintain than sequential programs. This paper introduces Kendo: a new software-only system that provides deterministic multithreading of parallel applications. Kendo enforces a deterministic interleaving of lock acquisitions and specially declared non-protected reads through a novel dynamically load-balanced deterministic scheduling algorithm. The algorithm tracks the progress of each thread using performance counters to construct a deterministic logical time that is used to compute an interleaving of shared data accesses that is both deterministic and provides good load balancing. Kendo can run on today’s commodity hardware while incurring only a modest performance cost. Experimental results on the SPLASH-2 applications yield a geometric mean overhead of only 16% when running on 4 processors. This low overhead makes it possible to benefit from Kendo even after an application is deployed. Programmers can start using Kendo today to program parallel applications that are easier to develop, debug, and test.


References in zbMATH (referenced in 7 articles )

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  1. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2018)
  2. Shinano, Yuji; Heinz, Stefan; Vigerske, Stefan; Winkler, Michael: FiberSCIP -- a shared memory parallelization of SCIP (2018)
  3. Mushtaq, Hamid; Al-Ars, Zaid; Bertels, Koen: Efficent and highly portable deterministic multithreading (DetLock) (2014) ioport
  4. Koch, Thorsten; Ralphs, Ted; Shinano, Yuji: Could we use a million cores to solve an integer program? (2012)
  5. Zhou, Xu; Lu, Kai; Wang, Xiaoping; Li, Xu: Exploiting parallelism in deterministic shared memory multiprocessing (2012) ioport
  6. Gay, David; Galenson, Joel; Naik, Mayur; Yelick, Kathy: Yada: straightforward parallel programming (2011) ioport
  7. Lu, Li; Scott, Michael L.: Toward a formal semantic framework for deterministic parallel programming (2011)