libhmsbeagle 2.1-2 source package in Ubuntu
Changelog
libhmsbeagle (2.1-2) unstable; urgency=medium
* debian/libhmsbeagle-dev.links: Link to non-versioned include files since
it is used that way in mrbayes (and probably others)
-- Andreas Tille <email address hidden> Mon, 13 Jan 2014 17:00:56 +0100
Upload details
- Uploaded by:
- Debian Med
- Uploaded to:
- Sid
- Original maintainer:
- Debian Med
- Architectures:
- linux-any
- Section:
- libs
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section | |
|---|---|---|---|---|
| Trusty | release | universe | libs |
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| libhmsbeagle_2.1-2.dsc | 1.6 KiB | 8cdc2df718b96cdf489c62b77c76f3c87b97a87988a06f4ae4214ddb11a2ea1c |
| libhmsbeagle_2.1.orig.tar.xz | 253.9 KiB | 1147179ec5f9389a1054dbe238fd99d70376a499353f2c1b34c76d899a0fa481 |
| libhmsbeagle_2.1-2.debian.tar.gz | 40.2 KiB | 3ca90de9d0bdda92774ed8685d7e6e296479514aec791c730073894d440debcb |
Available diffs
- diff from 2.1-1 to 2.1-2 (420 bytes)
No changes file available.
Binary packages built by this source
- libhmsbeagle-dev: No summary available for libhmsbeagle-dev in ubuntu utopic.
No description available for libhmsbeagle-dev in ubuntu utopic.
- libhmsbeagle-java: No summary available for libhmsbeagle-java in ubuntu utopic.
No description available for libhmsbeagle-java in ubuntu utopic.
- libhmsbeagle1: High-performance lib for Bayesian and Maximum Likelihood phylogenetics
BEAGLE is a high-performance library that can perform the core calculations at
the heart of most Bayesian and Maximum Likelihood phylogenetics packages. It
can make use of highly-parallel processors such as those in graphics cards
(GPUs) found in many PCs.
.
The project involves an open API and fast implementations of a library for
evaluating phylogenetic likelihoods (continuous time Markov processes) of
biomolecular sequence evolution.
.
The aim is to provide high performance evaluation 'services' to a wide range
of phylogenetic software, both Bayesian samplers and Maximum Likelihood
optimizers. This allows these packages to make use of implementations that
make use of optimized hardware such as graphics processing units.
