Electron tomography of complex biological specimens on the Grid
Future Generation Computer Systems
Parameter optimization in 3D reconstruction on a large scale grid
Parallel Computing
Grid-Enabled BLASTZ: Application to Comparative Genomics
Journal of VLSI Signal Processing Systems
Experiences with developing and deploying dynamic BLAST
Proceedings of the 15th ACM Mardi Gras conference: From lightweight mash-ups to lambda grids: Understanding the spectrum of distributed computing requirements, applications, tools, infrastructures, interoperability, and the incremental adoption of key capabilities
BLAST Application with Data-Aware Desktop Grid Middleware
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Bioinformatics algorithm development for Grid environments
Journal of Systems and Software
Exploiting performance characterization of BLAST in the grid
Cluster Computing
A framework for readapting and running bioinformatics applications in the cloud
Proceedings of the 2012 ACM Research in Applied Computation Symposium
An improved partitioning mechanism for optimizing massive data analysis using MapReduce
The Journal of Supercomputing
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Improvements in the performance of processors and networks have made it feasible to treat collections of workstations, servers, clusters and supercomputers as integrated computing resources or Grids. However, the very heterogeneity that is the strength of computational and data Grids can also make application development for such an environment extremely difficult. Application development in a Grid computing environment faces significant challenges in the form of problem granularity, latency and bandwidth issues as well as job scheduling. Currently existing Grid technologies limit the development of Grid applications to certain classes, namely, embarrassingly parallel, hierarchical parallelism, work flow and database applications. Of all these classes, embarrassingly parallel applications are the easiest to develop in a Grid computing framework. The work presented here deals with creating a Grid-enabled, high-throughput, standalone version of a bioinformatics application, BLAST, using Globus as the Grid middleware. BLAST is a sequence alignment and search technique that is embarrassingly parallel in nature and thus amenable to adaptation to a Grid environment. A detailed methodology for creating the Grid-enabled application is presented, which can be used as a template for the development of similar applications. The application has been tested on a ‘mini-Grid’ testbed and the results presented here show that for large problem sizes, a distributed, Grid-enabled version can help in significantly reducing execution times. Copyright © 2005 John Wiley & Sons, Ltd.