p-MDAG - A Parallel MDAG Approach

Joubert de Castro Lima, Celso Massaki Hirata

2010

Abstract

In this paper, we present a novel parallel full cube computation approach, named p-MDAG. The p-MDAG approach is a parallel version of MDAG sequential approach. The sequential MDAG approach outperforms the classic Star approach in dense, skewed and sparse scenarios. In general, the sequential MDAG approach is 25-35% faster than Star, consuming, on average, 50% less memory to represent the same data cube. The p-MDAG approach improves the runtime while keeping the low memory consumption; it uses an attribute-based data cube decomposition strategy which combines both task and data parallelism. The p-MDAG approach uses the dimensions attribute values to partition the data cube. It also redesigns the MDAG sequential algorithms to run in parallel. The p-MDAG approach provides both good load balance and similar sequential memory consumption. Its logical design can be implemented in shared-memory, distributed-memory and hybrid architectures with minimal adaptation.

Paper Citation

in Harvard Style

de Castro Lima J. and Hirata C. (2010). p-MDAG - A Parallel MDAG Approach . In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8425-04-1, pages 322-331. DOI: 10.5220/0003017703220331

in Bibtex Style

@conference{iceis10,
author={Joubert de Castro Lima and Celso Massaki Hirata},
title={p-MDAG - A Parallel MDAG Approach},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2010},
pages={322-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003017703220331},
isbn={978-989-8425-04-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - p-MDAG - A Parallel MDAG Approach
SN - 978-989-8425-04-1
AU - de Castro Lima J.
AU - Hirata C.
PY - 2010
SP - 322
EP - 331
DO - 10.5220/0003017703220331