By Jeffrey D. Krause at Shodor, Durham, North Carolina
and Michael Ly at the University of Illinois, Champaign-Urbana, Illinois
With Contributions from Aaron Weeden and Jennifer Houchins
Shodor, Durham, North Carolina
This module explores the inner workings of the BLAST similarity search tool, considering the
algorithm and the impact of various search conditions and settings on performance. Various
approaches to parallelizing the computation and their performance impacts are considered.
Benchmarking of the mpiBLAST parallel code is carried out at different scales.
Three different versions of BLAST are run in this module:
The module documents can be downloaded below.
Parallel_BLAST.doc : MS Word document describing: 1) the biology of sequence similarity, 2) the basic BLAST algorithm, 3) an activity to characterize the performance of NCBI's server-based BLAST, 4) an activity to build and benchmark of NCBI's stand-alone BLAST, and 5) an activity to build, benchmark and scale mpiBLAST.
Parallel BLAST (PDF) : The module document in PDF format.