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| author | Joe Hunkeler <jhunkeler@gmail.com> | 2015-04-15 20:54:15 -0400 |
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| committer | Joe Hunkeler <jhunkeler@gmail.com> | 2015-04-15 20:54:15 -0400 |
| commit | bd8885b906948160c405d68e12e5901275b45eee (patch) | |
| tree | 82fc6d5cc4bc174598be7ac383a5c6992c1309cd | |
| parent | 2a317a9f1e1ac288039104ad835b73481e914420 (diff) | |
| download | ur_optimize-bd8885b906948160c405d68e12e5901275b45eee.tar.gz | |
README.md edited online with Bitbucket
| -rw-r--r-- | README.md | 2 |
1 files changed, 1 insertions, 1 deletions
@@ -1,6 +1,6 @@ # Why do I want to use ur_optimize? #
-The version of ATLAS bundled with Ureka (http://ssb.stsci.edu/ureka) is designed to work on a large number of CPUs, therefore certain operations requiring linear algebra may perform inadequately to your needs.
+The version of ATLAS bundled with Ureka (http://ssb.stsci.edu/ureka) is not designed to work on a large number of CPUs, therefore certain operations requiring linear algebra may perform inadequately to your needs.
`ur_optimize` rebuilds the underlying ATLAS/LaPACK/BLAS stack to be tailored for your CPU's architecture. After that, the NumPy/SciPy stack is recompiled and linked against the new ATLAS implementation in order to take advantage of these optimizations.
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