Abstract
Concurrent object-oriented programming languages are an attractive approach for programming massively-parallel machines. However, exploiting object-level concurrency is problematic as the linkage and communication overhead can overwhelm the benefits of the fine-grained concurrency. Our approach achieves efficient execution by tuning the grain size, matching the execution grain size to that efficiently supportable by the architecture. To verify the feasibility of grain-size tuning, we study the invocation locality of a collection of object-oriented programs. The results suggest that local constraints on placement combined with code specialization can produce a significant increase in execution grain size. We describe several compile-time analyses which identify opportunities to increase grain size. These analyses identify static relationships between objects and enable transformations to reduce invocation cost. Some initial measurements are presented.
The research described in this paper was supported in part by National Science Foundation grant CCR-9209336, Office of Naval Research grant N00014-92-J-1961, and National Aeronautics and Space Administration grant NAG 1-613. Additional support has been provided by a generous special-purpose grant from the AT&T Foundation.
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Chien, A., Feng, W., Karamcheti, V., Plevyak, J. (1993). Techniques for efficient execution of fine-grained concurrent programs. In: Banerjee, U., Gelernter, D., Nicolau, A., Padua, D. (eds) Languages and Compilers for Parallel Computing. LCPC 1992. Lecture Notes in Computer Science, vol 757. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57502-2_46
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DOI: https://doi.org/10.1007/3-540-57502-2_46
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