List of Open Source Software which can be built on Fugaku

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Spack will be used to manage open source software packages on Fugaku. Fugaku users can easily use pre-installed packages and built packages based on Spack recipes. The following list shows the results of building/compiling packages for aarch64 according to the Spack recipes. Note that the results in this list do not guarantee that each package will work properly. On the other hand, Fujitsu will provide the following packages compiled with Fujitsu compiler on Fugaku as "external" packages, of which Spack can be aware.
  • OpenJDK 11
  • Ruby 2.6.5 or later
  • Python2 2.7.15
  • Python3 3.6.8
  • Numpy 1.14.3
  • SciPy 1.0.0
  • Eclipse IDE 2019-09 R Packages
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r-bfast

Package

r-bfast

Description

Breaks for Additive Season and Trend. Decomposition of time series into
trend, seasonal, and remainder components with methods for detecting and
characterizing abrupt changes within the trend and seasonal components.
'BFAST' can be used to analyze different types of satellite image time
series and can be applied to other disciplines dealing with seasonal or
non-seasonal time series, such as hydrology, climatology, and
econometrics. The algorithm can be extended to label detected changes
with information on the parameters of the fitted piecewise linear
models. 'BFAST' monitoring functionality is described in Verbesselt et
al. (2010) <doi:10.1016/j.rse.2009.08.014>. 'BFAST monitor' provides
functionality to detect disturbance in near real-time based on 'BFAST'-
type models, and is described in Verbesselt et al. (2012)
<doi:10.1016/j.rse.2012.02.022>. 'BFAST Lite' approach is a flexible
approach that handles missing data without interpolation, and will be
described in an upcoming paper. Furthermore, different models can now be
used to fit the time series data and detect structural changes (breaks).

Note


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