Abstract
In this paper we investigate the issue of automatically identifying the “natural” degree of parallelism of an application using software transactional memory (STM), i.e., the workload-specific multiprogramming level that maximizes application’s performance. We discuss the importance of adapting the concurrency level to the workload in two different scenarios, a shared-memory and a distributed STM infrastructure. We propose and evaluate two alternative self-tuning methodologies, explicitly tailored for the considered scenarios. In shared-memory STM, we show that lightweight, black-box approaches relying solely on on-line exploration can be extremely effective. For distributed STMs, we introduce a novel hybrid approach that combines model-driven performance forecasting techniques and on-line exploration in order to take the best of the two techniques, namely enhancing robustness despite model’s inaccuracies, and maximizing convergence speed towards optimum solutions.
This work has been partially supported by the projects “Cloud-TM” and “ParaDIME” (co-financed by the European Commission through the contract no. 257784 and 318693), project specSTM (PTDC/EIA-EIA/122785/2010), the COST Action Euro-TM (IC1001) and by FCT (INESC-ID multiannual funding) through the PEst-OE/EEI/LA0021/2011 Program Funds.
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References
Herlihy, M., Moss, J.E.B.: Transactional memory: Architectural support for lock-free data structures. In: Proc. of ISCA (1993)
Harris, T., Larus, J.R., Rajwar, R.: Transactional Memory, 2nd edn. Synthesis Lectures on Computer Architecture. Morgan & Claypool Publisher (2010)
Reimer, N., Haenssgen, S., Tichy, W.F.: Dynamically adapting the degree of parallelism with reflexive programs. In: Saad, Y., Yang, T., Ferreira, A., Rolim, J.D.P. (eds.) IRREGULAR 1996. LNCS, vol. 1117, Springer, Heidelberg (1996)
Heiss, H.U., Wagner, R.: Adaptive load control in transaction processing systems. In: Proc. of VLDB (1991)
Schroeder, B., Harchol-Balter, M., Iyengar, A., Nahum, E., Wierman, A.: How to determine a good multi-programming level for external scheduling. In: Proc. of ICDE (2006)
Abouzour, M., Salem, K., Bumbulis, P.: Automatic tuning of the multiprogramming level in Sybase SQL Anywhere. In: Proc. of ICDE Workshops (2010)
Yoo, R.M., Lee, H.H.S.: Adaptive transaction scheduling for transactional memory systems. In: Proc. of SPAA (2008)
Mohammad, A., Mikel, L., Christos, K., Kim, J., Chris, K., Ian, W.: Robust adaptation to available parallelism in transactional memory applications. HIPEAC Journal (2008)
Ghanbari, S., Soundararajan, G., Chen, J., Amza, C.: Adaptive learning of metric correlations for temperature-aware database provisioning. In: Proc. of ICAC (2007)
Zhang, Q., Cherkasova, L., Smirni, E.: A regression-based analytic model for dynamic resource provisioning of multi-tier applications. In: Proc. of ICAC (2007)
di Sanzo, P., Ciciani, B., Quaglia, F., Romano, P.: A performance model of multi-version concurrency control. In: Proc. of MASCOTS (2008)
Heindl, A., Pokam, G., Adl-Tabatabai, A.R.: An analytic model of optimistic software transactional memory. In: Proc. of ISPASS (2009)
Dragojevic, A., Guerraoui, R.: Predicting the scalability of an stm: A pragmatic approach (2010)
Rughetti, D., Di Sanzo, P., Ciciani, B., Quaglia, F.: Machine learning-based self-adjusting concurrency in software transactional memory systems. In: Proc. of MASCOTS (2012)
Cao Minh, C., Chung, J., Kozyrakis, C., Olukotun, K.: STAMP: Stanford transactional applications for multi-processing. In: Proc. of IISWC (2008)
Schenker, J.: Optimistic Synchronization and the Natural Degree of Parallelism of Concurrent Applications — MSc Thesis (June 2012)
Couceiro, M., Romano, P., Carvalho, N., Rodrigues, L.: D2stm: Dependable distributed software transactional memory. In: Proc. of PRDC (2009)
Narasimha Raghavan, R.V.: Balancing the communication load of state transfer in replicated systems. In: Proc. of SRDS (2011)
Jiménez-Peris, R., Patiño-Martínez, M., Alonso, G.: Non-intrusive, parallel recovery of replicated data. In: Proc. of SRDS (2002)
Elnikety, S., Dropsho, S., Cecchet, E., Zwaenepoel, W.: Predicting replicated database scalability from standalone database profiling. In: Proc. of EuroSys (2009)
Didona, D., Romano, P., Peluso, S., Quaglia, F.: Transactional auto scaler: elastic scaling of in-memory transactional data grids. In: Proc. of ICAC (2012)
Singh, R., Sharma, U., Cecchet, E., Shenoy, P.: Autonomic mix-aware provisioning for non-stationary data center workloads. In: Proc. of ICAC (2010)
Francesco, M., Manik, S.: Infinispan Data Grid Platform. Packt Publishing (2012)
Red Hat/JBoss: JBoss Infinispan (2011), http://www.jboss.org/infinispan
TPC Council: TPC-C Benchmark (2011), http://www.tpc.org/tpcc
Yu, P.S., Dias, D.M., Lavenberg, S.S.: On the analytical modeling of database concurrency control. ACM Journal (1993)
Quinlan, J.R.: Rulequest Cubist, http://www.rulequest.com/cubist-info.html
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers Inc. (1993)
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Didona, D., Felber, P., Harmanci, D., Romano, P., Schenker, J. (2013). Identifying the Optimal Level of Parallelism in Transactional Memory Applications. In: Gramoli, V., Guerraoui, R. (eds) Networked Systems. NETYS 2013. Lecture Notes in Computer Science, vol 7853. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40148-0_17
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