How to write parallel programs: a guide to the perplexed
ACM Computing Surveys (CSUR)
Parallel mining algorithms for generalized association rules with classification hierarchy
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Parallel programming: techniques and applications using networked workstations and parallel computers
A comparison of receiver-initiated and sender-initiated adaptive load sharing (extended abstract)
SIGMETRICS '85 Proceedings of the 1985 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Dynamic Load Balancing for Parallel Association Rule Mining on Heterogenous PC Cluster Systems
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Modified PrefixSpan Method for Motif Discovery in Sequence Databases
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Parallel tree-projection-based sequence mining algorithms
Parallel Computing
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
Parallel processing for stepwise generalisation method on multi-core PC cluster
International Journal of Knowledge and Web Intelligence
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In order to extract the frequent patterns that can become motif at high speed from amino acid sequences, we are developing the parallel Modified PrefixSpan with the distributed worker paradigm. This paper presents a new dynamic load balancing technique for the parallel Modified PrefixSpan with the distributed worker paradigm and its performance evaluation. The characteristics of the dynamic load balancing are the small-grain task and the Cache-based Random Steal schema. This paper explains these characteristics and presents performance evaluations with the PC cluster of 100 nodes.