Abstract
The multicore era has increased the need for highly parallel software. Since automatic parallelization turned out ineffective for many production codes, the community hopes for the development of tools that may assist parallelization, providing hints to drive the parallelization process. In our previous work, we had designed Tareador, a tool based on dynamic instrumentation that identifies potential task-based parallelism inherent in applications. Also, we showed how a programmer can use Tareador to explore the potential of different parallelization strategies. In this paper, we build up on our previous work by automating the process of exploring parallelism. We have designed an environment that, given a sequential code and configuration of the target parallel architecture, iteratively runs Tareador to find an efficient parallelization strategy. We propose an autonomous algorithm based on simple metrics and a cost function. The algorithm finds an efficient parallelization strategy and provides the programmer with sufficient information to turn that parallelization strategy into an actual parallel program.
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References
Benkner, S.: Vfc: The vienna fortran compiler. Scientific Programming 7(1), 67–81 (1999)
Bik, A., Girkar, M., Grey, P., Tian, X.: Efficient exploitation of parallelism on pentium iii and pentium 4 processor-based systems (2001)
Critical Blue. Prism, http://www.criticalblue.com/ (active on June 27, 2013)
Blume, W., Doallo, R., Eigenmann, R., Grout, J., Hoeflinger, J., Lawrence, T., Lee, J., Padua, D.A., Paek, Y., Pottenger, W.M., Rauchwerger, L., Tu, P.: Parallel programming with polaris. IEEE Computer 29(12), 78–82 (1996)
Intel Corporation. Intel Parallel Advisor, http://software.intel.com/en-us/intel-advisor-xe (active on June 27, 2013)
Duran, A., Ayguadé, E., Badia, R.M., Labarta, J., Martinell, L., Martorell, X., Planas, J.: Ompss: a proposal for programming heterogeneous multi-core architectures. Parallel Processing Letters 21(2), 173–193 (2011)
Vector Fabrics. Pareon, http://www.vectorfabrics.com/products (active on June 27, 2013)
Garcia, S., Jeon, D., Louie, C.M., Taylor, M.B.: Kremlin: rethinking and rebooting gprof for the multicore age. In: PLDI, pp. 458–469 (2011)
Jost, G., Labarta, J., Gimenez, J.: Paramedir: A tool for programmable performance analysis. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3036, pp. 466–469. Springer, Heidelberg (2004)
Lattner, C., Adve, V.: LLVM: A compilation framework for lifelong program analysis and transformation, San Jose, CA, USA, pp. 75–88 (March 2004)
Mak, J., Faxén, K.-F., Janson, S., Mycroft, A.: Estimating and Exploiting Potential Parallelism by Source-Level Dependence Profiling. In: D’Ambra, P., Guarracino, M., Talia, D. (eds.) Euro-Par 2010, Part I. LNCS, vol. 6271, pp. 26–37. Springer, Heidelberg (2010)
Nethercote, N., Seward, J.: Valgrind, http://valgrind.org/ (active on June 27, 2013)
Pheatt, C.: Intel threading building blocks. J. Comput. Sci. Coll. 23(4), 298–298 (2008)
Pillet, V., Labarta, J., Cortes, T., Girona, S.: PARAVER: A Tool to Visualize and Analyze Parallel Code. In: WoTUG-18 (1995)
Subotic, V., Ferrer, R., Sancho, J.C., Labarta, J., Valero, M.: Quantifying the Potential Task-Based Dataflow Parallelism in MPI Applications. In: Jeannot, E., Namyst, R., Roman, J. (eds.) Euro-Par 2011, Part I. LNCS, vol. 6852, pp. 39–51. Springer, Heidelberg (2011)
Wilson, R.P., French, R.S., Wilson, C.S., Amarasinghe, S.P., Anderson, J.-A.M., Tjiang, S.W.K., Liao, S.-W., Tseng, C.-W., Hall, M.W., Lam, M.S., Hennessy, J.L.: Suif: An infrastructure for research on parallelizing and optimizing compilers. SIGPLAN Notices 29(12), 31–37 (1994)
Zhang, X., Navabi, A., Jagannathan, S.: Alchemist: A transparent dependence distance profiling infrastructure. In: CGO 2009 (2009)
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Subotic, V., Ayguadé, E., Labarta, J., Valero, M. (2014). Automatic Exploration of Potential Parallelism in Sequential Applications. In: Kunkel, J.M., Ludwig, T., Meuer, H.W. (eds) Supercomputing. ISC 2014. Lecture Notes in Computer Science, vol 8488. Springer, Cham. https://doi.org/10.1007/978-3-319-07518-1_10
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DOI: https://doi.org/10.1007/978-3-319-07518-1_10
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