research-article

Mapping Datalog Program Execution to Networks of Processors

Authors:

Abraham Silberschatz,

Shalom TsurAuthors Info & Claims

IEEE Transactions on Knowledge and Data Engineering, Volume 7, Issue 3

Pages 351 - 361

https://doi.org/10.1109/69.390243

Published: 01 June 1995 Publication History

Abstract

The problem of mapping the parallel bottom up execution of Datalog programs to an interconnected network of processors is studied. The parallelization is achieved by using hash functions that partition the set of instantiations for the rules. We first examine this problem in an environment where the number of processors and the interconnection topology is known, and communication between program segments residing at non-adjacent processors is not permitted. An algorithm is presented that decides whether a given Datalog program can be mapped onto such an architecture. We then relax the constraint on the architecture by allowing program segments residing at non-adjacent processors to communicate. A theory of approximate mappings is developed, and an algorithm to obtain the closest approximate mapping of a given Datalog program onto a given architecture is presented.

References

[1]

K. R Apt, “Introduction to logic programming,” Tech. Report TR-87-35, Dept. of Computer Sciences, The Univ. of Texas at Austin, 1988.]]

Digital Library

[2]

F. Bancilhon, “Naive evaluation of recursively defined relations,” MCC Tech. Report No DB-004-85.]]

[3]

F. Bancilhon and R. Ramakrishnan, “An amateur’s introduction to recursive query processing strategies,” Proc. of the 1986 ACM SIGMOD Int’l. Conf. on the Management ofData.]]

Digital Library

[4]

S. Cohen and O. Wolfson, “Why a single parallelization strategy is not enough in knowledgebases,”, Proc of the 8th ACM Symp. on Principles of Database Systems, March 1989.]]

Digital Library

[5]

S. Ganguly, A. Silberschatz, and S. Tsur., “A framework for the parallel evaluation of datalog queries,” Proc. of the 1990 ACM SIGMOD Conf. on Management of Data, 1990.]]

Digital Library

[6]

J. W. Lloyd, Foundations of Logic Programming Springer-Verlag, Second edition, 1987.]]

Digital Library

[7]

R. Ramakrishnan and J.D. Ullman, “A survey of research on deductive database systems,” manuscript, June 1993.]]

[8]

J. Seib and G. Lausen, “Parallelizing Datalog programs by generalized pivoting,” Proc. of the 1991 Symp. on Principles of Database Sytems.]]

Digital Library

[9]

S. Stolfo, D. Miranker, and M. Proco, “A simple preprocessing scheme to extract and balance implicit parallelismin the concurrent match of production rules,” Int’l. Workshop on Fifth Generation Computer Architectures, 1985.]]

Digital Library

[10]

S. Stolfo, Mills, Pasik, and Van Biema, “Let’s stop the dust from collecting on OPS5,” Concepts and Characteristics of Knowledge-Based Systems, North-Holland, 1986.]]

[11]

S. Tsur, “Applications of deductive dtabase systems,” Proc. of the 35th IEEE Comp. Soc. Int’l. Conf., 1990.]]

[12]

S. Tsur, F. Olken, and D. Naor, “Deductive databases for genomic mapping,” NACLP90 Workshop on Deductive Database Applications, 1990.]]

[13]

S. Tsur, “Data dredging,” IEEE Data Eng. Bull., 1990.]]

Digital Library

[14]

S. Tsur and C. Zaniolo, “LDL: a logic-based data language,” Proc of the Int’l. Conf. on Very Large Databases, 1986.]]

Digital Library

[15]

J. Ullman, “Principles of database and knowledge base systems,” Computer Science Press, 1989.]]

Digital Library

[16]

O. Wolfson and A. Silberschatz, “Distributed processing of logic programs,” Proc. of the 1988 ACM SIGMOD Int’l. Conf. on Management of Data, 1988.]]

Digital Library

[17]

O. Wolfson, “Sharing the load of logic program evaluation,” Proc. of the 1989 Int’l. Symposium on Databases in Parallel and DistributedSystems, 1989.]]

Digital Library

[18]

O. Wolfson and A. Ozeri, “A new paradigm for distributed rule processing,” Proc. of the 1990 ACM SIGMOD Int’l. Conf. on Management of Data, 1990.]]

Digital Library

Cited By

Yang MShkapsky AZaniolo C(2017)Scaling up the performance of more powerful Datalog systems on multicore machinesThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-016-0448-z26:2(229-248)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1007/s00778-016-0448-z

Mapping Datalog Program Execution to Networks of Processors
1. Theory of computation
  1. Logic

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cover image IEEE Transactions on Knowledge and Data Engineering

IEEE Transactions on Knowledge and Data Engineering Volume 7, Issue 3

June 1995

161 pages

ISSN:1041-4347

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Copyright © Copyright © 1995 IEEE. All Rights Reserved.

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IEEE Educational Activities Department

United States

Publication History

Published: 01 June 1995

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Cited By

Yang MShkapsky AZaniolo C(2017)Scaling up the performance of more powerful Datalog systems on multicore machinesThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-016-0448-z26:2(229-248)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1007/s00778-016-0448-z

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