Abstract
We have developed a technique that maps logic programs (database queries) onto a dataflow graph to support static scheduling in a multiprocessor environment [8]. A dataflow graph explicitly shows the execution paths, data dependence, and synchronization points in a query. The scheme attempts to properly group fine grain operations — select and join — into coarser grains as a means to exploit parallelism while minimizing the communication costs. This leads to a higher hardware utilization and performance.
In this paper, we expand the scope of our scheme by using a set of heuristic rules to assign processes to available processors more efficiently. This is made possible by analyzing the probability of success of each branch in the logic program. In a logic program, the early scheduling and execution of some branches with higher probability of failure leads to a higher possibility to eliminate many other branches. On the other hand, early execution of some branches with higher probability of success can lead to a higher hardware utilization. The extended scheme has been simulated, and its performance has been compared against the original model and the traditional parallel execution paradigm of the logic program.
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Hurson, A.R., Jun, BU. (1995). Optimization scheme on execution of logic program in a dataflow environment. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1995. Lecture Notes in Computer Science, vol 964. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60222-4_110
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DOI: https://doi.org/10.1007/3-540-60222-4_110
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