Performance analysis and optimization of AMGA for the large‐scale virtual screening

Abstract

This paper addresses performance issues on ARDA Metadata Grid Application (AMGA) and presents new techniques to improve the throughput of AMGA for the WISDOM environment. The first issue is a performance degradation problem when AMGA is used as a metadata service for task retrieval in the WISDOM environment. To deal with the issue, a new AMGA operation designed to reduce the communication overhead required to retrieve a task from AMGA is proposed. According to a performance study conducted with the new operation, the throughput of task retrieval using the proposed operation can be as much as 70 times higher than the throughput when using the existing AMGA operations. The second issue is an AMGA throughput issue in large‐scale grid‐enabled applications such as WISDOM, where it is not uncommon that thousands of jobs running on grid nodes access the AGMA service simultaneously. To address this issue, integration of a load‐balancing technique and a DB connection pool technique into the AMGA are proposed. Test results demonstrate that the performance can be improved linearly in proportion to the number of AMGA servers set up for load balancing; the performance improvement continues until the performance limit of the backend database system is reached. Copyright © 2009 John Wiley & Sons, Ltd.

Conceptual Design of a Data Repository for the Korea LTER Community

“…First, we had benchmarked various existing tools to build K-ecohub. AMGA [10] is a metadata catalog, which provides access to metadata for files stored on the Grid. It is well fit to support data scalability, but it requires a lot of development efforts to take advantage of this software in the long-term ecological field.…”

Multiobjective Design Optimization Framework for Multicomponent System with Complex Nonuniform Loading

“…erefore, an accurate optimal algorithm, which can precisely search for Pareto optimal frontier and acquire nondominated solutions, is urgently required. At present, a variety of multiobjective optimization algorithms are developed, such as multi-island genetic algorithm (MIGA) [31][32][33], neighbourhood cultivation genetic algorithm (NCGA) [34,35], the second generation of nondominated sorting genetic algorithm (NSGA-II) [36][37][38], and archive microgenetic algorithm (AMGA) [39,40]. Among them, owing to the virtues of nondominated sorting strategy and elitist retention strategy, NSGA-II has been widely used in MODO problems.…”

Design and implementation of AMGA metadata catalog system for interoperability in European middleware initiative

“…It also offers security functions including X.509-based certificates, VOMS support, Grid-proxy certificates, and detailed ACL. [1][2] [4] The European Middleware Initiative (EMI), which is the result of the collaboration of four major middleware systems in Europe, aims to expand and improve interoperability and deployment over a massive distributed infrastructure, and, at the same time, to construct a model for the future maintenance and evolution of middleware components. In order to register in the EMI repository, a candidate must comply with EMI development policy.…”