diff --git a/salomon.csv b/salomon.csv index 9c4195df78bfe3988df08ff5d7acdf0f3dd5799f..832fc54fa4305f63ac8af8b3b0c858227a1866db 100644 --- a/salomon.csv +++ b/salomon.csv @@ -225,6 +225,7 @@ CORALbenchmark/1.00-foss-2016a,2 CP2K/2.6.0-intel-2015b,2 CP2K/5.1,2 Cube/4.3.4-intel-2015b,2 +Cube/4.3.5,2 CUDA/7.5.18,2 CUDA/8.0.61,2 CUDA/9.1.85,2 @@ -244,6 +245,7 @@ DDT/4.2,2 DDT/5.0.1,2 Debian/8.0,2 Debian/8.0-shell,2 +decorator/4.2.1-Py-3.6,2 deMonNano/4.3.6,2 Digimat/5.0.1-COM,2 Digimat/5.0.1-EDU,2 @@ -1140,6 +1142,7 @@ nettle/3.2-intel-2017a,2 nettle/3.3-foss-2017a,2 nettle/3.3-intel-2017a,2 networkx/1.11-Python-2.7.13,2 +networkx/2.1-Py-3.6,2 NLopt/2.4.2,2 NLopt/2.4.2-intel-2017a,2 NodeJS/6.10.1-foss-2016a,2 @@ -1174,6 +1177,7 @@ Octave/4.2.1-intel-2017a-without-X11,2 Octopus/7.1-intel-2017a,2 OPARI2/1.1.4-intel-2015b,2 OPARI2/2.0,2 +OPARI2/2.0.2,2 OpenBabel/2.4.1-Python-2.7.13,2 OpenBLAS/0.2.14-GNU-4.9.3-2.25-LAPACK-3.5.0,2 OpenBLAS/0.2.14-GNU-5.1.0-2.25-LAPACK-3.5.0,2 @@ -1228,6 +1232,7 @@ OSPRay/1.3.0-intel-2017a,2 OTF2/1.4-intel-2015b,2 OTF2/2.0,2 OTF2/2.0-intel-2015b-mic,2 +OTF2/2.1,2 p4vasp/0.3.30,2 palettable/3.1.0-Py-3.6,2 pandas/0.22.0-Py-3.6,2 @@ -1261,6 +1266,7 @@ PCRE/8.37-foss-2015g,2 PCRE/8.39-intel-2017.00,2 PCRE/8.40,2 PDT/3.18.1,2 +PDT/3.24,2 perfboost/1.0,2 perfcatcher/1.0,2 PerformanceReports/5.1-43967,2 diff --git a/salomon.md b/salomon.md index 86131cb3e56c8c59da8c1ea756c3add3bb33f67e..895ecb46b9436dcf7ac8cb0b46d4af9286d4591d 100644 --- a/salomon.md +++ b/salomon.md @@ -335,6 +335,7 @@ | [perfcatcher](http://www.sgi.com/) | Light-weight application profiler for SGI MPI | | [PerfReports](http://www.allinea.com/") | helps you address the question of quality of utilization. It provides a one page HTML report - collecting, analyzing and reporting the key metrics that impact performance. It can be used without changing either the source code or the application - removing the barriers and opening access to everyon | | [PerfSuite](http://perfsuite.ncsa.illinois.edu/") | PerfSuite is a collection of tools, utilities, and libraries for software performance analysis where the primary design goals are ease of use, comprehensibility, interoperability, and simplicity. This software can provide a good "entry point" for more detailed performance analysis and can help point the way towards selecting other tools and/or techniques using more specialized software if necessary (for example, tools/libraries from academic research groups or third-party commercial software | +| [Score-P](http://www.vi-hps.org/projects/score-p//) | Score-P offers the user a maximum of convenience by supporting a number of analysis tools. Currently, it works with Periscope, Scalasca, Vampir, and Tau and is open for other tools. Score-P comes together with the new Open Trace Format Version 2, the Cube4 profiling format and the Opari2 instrumenter (see below). Score-P is available under the New BSD Open Source license. | | [Vampir](http://www.vampir.eu) | The Vampir software tool provides an easy-to-use framework that enables developers to quickly display and analyze arbitrary program behavior at any level of detail. The tool suite implements optimized event analysis algorithms and customizable displays that enable fast and interactive rendering of very complex performance monitoring data. | | [VampirServer](http://www.vampir.eu) | The Vampir software tool provides an easy-to-use framework that enables developers to quickly display and analyze arbitrary program behavior at any level of detail. The tool suite implements optimized event analysis algorithms and customizable displays that enable fast and interactive rendering of very complex performance monitoring data. | @@ -369,6 +370,7 @@ | [certifi](https://pypi.python.org/pypi/certifi) | Python package for providing Mozillas CA Bundle. | | [click](https://pypi.python.org/pypi/click) | A simple wrapper around optparse for powerful command line utilities. | | [cycler](https://matplotlib.org/cycler) | Composable style cycles. | +| [decorator](https://pypi.python.org/pypi/decorator) | Better living through Python with decorators. | | [Flask](https://pypi.python.org/pypi/flask) | A microframework based on Werkzeug, Jinja2 and good intentions. | | [h5py](http://www.h5py.org/) | HDF5 for Python (h5py) is a general-purpose Python interface to the Hierarchical Data Format library, version 5. HDF5 is a versatile, mature scientific software library designed for the fast, flexible storage of enormous amounts of data. | | [itsdangerous](https://pypi.python.org/pypi/itsdangerous) | Various helpers to pass trusted data to untrusted environments and back. | @@ -382,6 +384,7 @@ | [monty](https://pypi.python.org/pypi/monty) | Monty is the missing complement to Python. | | [mpi4py](http://mpi4py.scipy.org/docs) | MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors. | | [mpmath](https://pypi.python.org/pypi/mpmath) | Python library for arbitrary-precision floating-point arithmetic. | +| [networkx](https://pypi.python.org/pypi/networkx) | NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. | | [numpy](http://www.numpy.org) | NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. | | [palettable](https://pypi.python.org/pypi/palettable) | Color palettes for Python. | | [pandas](https://pypi.python.org/pypi/pandas) | Powerful data structures for data analysis, time series,and statistics. | @@ -399,6 +402,7 @@ | [pyzmq](https://pypi.python.org/pypi/pyzmq) | Python bindings for 0MQ. | | [requests](https://pypi.python.org/pypi/requests) | Python HTTP for Humans. | | [ruamel.yaml](https://pypi.python.org/pypi/ruamel.yaml) | ruamel.yaml is a YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order | +| [scikit-image](http://scikit-learn.org/stable/index.html) | Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts. | | [scikit-learn](http://scikit-learn.org/stable/index.html) | Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts. | | [scipy](https://github.com/jupyter/testpath) | Test utilities for code working with files and commands | | [SCons](http://www.scons.org/) | SCons is a software construction tool. |