Double Inspection for Run-Time Loop Parallelization
The Inspector/Executor is well-known for parallelizing loops with irregular access patterns that cannot be analyzed statically. The downsides of existing inspectors are that it is hard to amortize their high run-time overheads by actually executing the loop in parallel, that they can only be applied to loops with dependencies that do not change during their execution and that they are often specifically designed for array codes and are in general not applicable in object oriented just-in-time compilation.
In this paper we present an inspector that inspects a loop twice to detect if it is fully parallelizable. It works for arbitrary memory access patterns, is conservative as it notices if changing data dependencies would cause errors in a potential parallel execution, and most importantly, as it is designed for current multicore architectures it is fast – despite of its double inspection effort: it pays off at its first use.
On benchmarks we can amortize the inspection overhead and outperform the sequential version from 2 or 3 cores onward.
Unable to display preview. Download preview PDF.
- 1.Bebenita, M., Brandner, F., Fahndrich, M., Logozzo, F., Schulte, W., Tillmann, N., Venter, H.: SPUR: a trace-based JIT compiler for CIL. In: Proc. OOPSLA 2010, ACM Intl. Conf. Object-Oriented Programming, Systems, Languages, and Applications, Reno, NV, pp. 708–725 (October 2010)Google Scholar
- 2.Chen, D.K., Torellas, J., Yew, P.C.: An efficient algorithm for the run-time parallelization of DOACROSS loops. In: Proc. ACM/IEEE Conf. Supercomp., Washington, DC, pp. 518–527 (November 1994)Google Scholar
- 4.Gupta, M., Nim, R.: Techniques for speculative run-time parallelization of loops. In: Proc. ACM/IEEE Conf. Supercomp., Melbourne, Australia, pp. 1–12 (July 1998)Google Scholar
- 5.Harris, T., Fraser, K.: Language support for lightweight transactions. In: Proc. OOPSLA 2003, ACM Intl. Conf. Object-Oriented Programming, Systems, Languages, and Applications, Anaheim, CA, pp. 388–402 (October 2003)Google Scholar
- 6.Kao, S.H., Yang, C.T., Tseng, S.S.: Run-time parallelization for loops. In: Proc. HICSS 1996, Hawaii Intl. Conf. System Sciences, Wailea, HI, vol. 1, pp. 233–242 (January 1996)Google Scholar
- 8.Leung, S.T., Zahorjan, J.: Improving the performance of runtime parallelization. In: Prof. PPoPP 1993, ACM SIGPLAN Symp. Principles and Practice of Parallel Programming, San Diego, CA, pp. 83–91 (May 1993)Google Scholar
- 10.Ponnusamy, R., Saltz, J., Choudhary, A.: Runtime compilation techniques for data partitioning and communication schedule reuse. In: Proc. ACM/IEEE Conf. Supercomp., Portland, OR, pp. 361–370 (November 1993)Google Scholar
- 14.Steffan, J.G., Colohan, C.B., Zhai, A., Mowry, T.C.: A scalable approach to thread-level speculation. In: Proc. Intl. Symp. Computer Architecture, Vancouver, Canada, pp. 1–12 (June 2000)Google Scholar
- 15.Yang, C.T., Tseng, S.S., Kao, S.H., Hsieh, M.H., Jiang, M.F.: Run-time parallelization for partially parallel loops. In: Proc. Intl. Conf. Parallel and Distrib. Systems, Seoul, South Korea, pp. 308–313 (December 1997)Google Scholar