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Commit d0e7e362 authored by easybuild's avatar easybuild
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Wed, 06 Sep 2017 14:45:03 +0200

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...@@ -526,6 +526,7 @@ Keras/2.0.5-Tensorflow-1.1.0-CUDA-7.5.18-Python-3.6.1,1 ...@@ -526,6 +526,7 @@ Keras/2.0.5-Tensorflow-1.1.0-CUDA-7.5.18-Python-3.6.1,1
Keras/2.0.5-Tensorflow-1.1.0-CUDA-8.0.44-Python-3.6.1,1 Keras/2.0.5-Tensorflow-1.1.0-CUDA-8.0.44-Python-3.6.1,1
Keras/2.0.5-Tensorflow-1.1.0-Python-3.6.1,1 Keras/2.0.5-Tensorflow-1.1.0-Python-3.6.1,1
Keras/2.0.5-Theano-1.2.0-Python-3.6.1,1 Keras/2.0.5-Theano-1.2.0-Python-3.6.1,1
MATLAB/2015b-EDU-test,1
METIS/5.1.0-intel-2017a,1 METIS/5.1.0-intel-2017a,1
METIS/5.1.0,1 METIS/5.1.0,1
MLD2P4/2.0-rc4-GCC-4.9.3-2.25,1 MLD2P4/2.0-rc4-GCC-4.9.3-2.25,1
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...@@ -276,6 +276,7 @@ ...@@ -276,6 +276,7 @@
| [ISL](http://isl.gforge.inria.fr/) | isl is a library for manipulating sets and relations of integer points bounded by linear constraints. | | [ISL](http://isl.gforge.inria.fr/) | isl is a library for manipulating sets and relations of integer points bounded by linear constraints. |
| Keras |   | | Keras |   |
| libcerf |   | | libcerf |   |
| MATLAB |   |
| METIS |   | | METIS |   |
| [MLD2P4](http://www.mld2p4.it) | MLD2P4 (Multi-Level Domain Decomposition Parallel Preconditioners Package based on PSBLAS) is a package of parallel algebraic multi-level preconditioners. It implements various versions of one-level additive and of multi-level additive and hybrid Schwarz algorithms. In the multi-level case, a purely algebraic approach is applied to generate coarse-level corrections, so that no geometric background is needed concerning the matrix to be preconditioned. The matrix is assumed to be square, real or complex, with a symmetric sparsity pattern. | | [MLD2P4](http://www.mld2p4.it) | MLD2P4 (Multi-Level Domain Decomposition Parallel Preconditioners Package based on PSBLAS) is a package of parallel algebraic multi-level preconditioners. It implements various versions of one-level additive and of multi-level additive and hybrid Schwarz algorithms. In the multi-level case, a purely algebraic approach is applied to generate coarse-level corrections, so that no geometric background is needed concerning the matrix to be preconditioned. The matrix is assumed to be square, real or complex, with a symmetric sparsity pattern. |
| MPFR |   | | MPFR |   |
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