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OVERVIEW
MPI-HMMER is an open source
MPI implementation of the HMMER protein sequence analysis
suite. The main search algorithms, hmmpfam and hmmsearch,
have been ported to MPI in order to provide high throughput
HMMER searches on modern computational clusters. We improve
on HMMER through sophisticated I/O, a se lf-contained
coordinator/worker model, and the easy inclusion of
accelerated architectures. This results in better
scalability while still maintaining the familiar user
interface.
MPI-HMMER Features:
- Improved database chunking strategy
- Portable across any POSIX operating system
- MPI implementation independent
- Vastly reduced computation times
- Improved query throughput
- Output nearly identical to standard HMMER
Upcoming Releases:
In the coming months we
plan to release several major enhancements to the MPI-HMMER
package. We currently have several research groups
implementing and porting MPI-HMMER to new platforms, and
introducing support for additional features. We plan to
introduce support for parallel IO to support users with
high-end parallel file systems.
Separately, researchers are porting the core of MPI-HMMER to
the Cell BE architecture with full support for SPEs. This
will allow the integration of Cell compute nodes along with
traditional general purpose processors to provide even
greater compute power.
In the long term, MPI-HMMER is undergoing a major
architectural overhaul designed to further improve the
scalability of the MPI-HMMER searches for large (massively)
parallel systems. More information regarding MPI-HMMER's
architectural improvements will be made available as it
approaches a usable, more stable, solution.
For researchers who find
MPI-HMMER a useful tool, we would appreciate being cited for
our work. Please use the following to cite MPI-HMMER:
J.P. Walters, B. Qudah, and
V. Chaudhary . Accelerating the HMMER Sequence Analysis
Suite Using Conventional Processors . In Proceedings of AINA
2006, Vienna Austria.
J. Landman, J. Ray, and J.P. Walters . Accelerating HMMer
searches on Opteron processors with minimally invasive
recoding. In Proceedings of HiPCOMB 2006, Vienna Austria.
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