work on software analysis #44 and DOE stack software analysis #45

/cc @HBarucq

.gitignore

@@ -31,4 +31,5 @@ docs/meetings/20220907_kickoff/beamertheme-trigon/source/x.log
 *.snm
 *.synctex.gz
 *.toc
-.DS_Store//
+.DS_Store
+

docs/software/analysis/analysis.py

@@ -0,0 +1,136 @@
+import pandas as pd
+import math
+
+# Specify the path to your Excel file
+file_path = 'doe.xlsx'
+
+# Read the Excel spreadsheet
+df = pd.read_excel(file_path)
+
+# Print the DataFrame
+print(df)
+
+solvers_list = [
+    "KokkosKernels",
+    "PETSc",
+    "PARDISO",
+    "Trilinos",
+    "SuperLU-Dist",
+    "STRUMPACK",
+    "Hypre",
+    "SPARSKIT",
+    "BLAS",
+    "SuperLU",
+    "SparsePACK",
+    "LAPACK"
+]
+math_list = ["SAMRAI", "STK", "MFEM", "UMR", "Portage", "Tangram", "Axom", "Overlink", "METIS", "ParMETIS", "Sculpt", "libigl"] 
+compilers_list = ["Kokkos", "RAJA Suite", "FleCSI", "Flang", "MPICH", "OpenMPI", "Legion", "PyKokkos", "KokkosRemoteMemorySpaces", "Fortran", "MPI", "C", "C++", "GCC", "HIP", "CUDA", "Python", "OpenMP", "Intel Compiler Suite", "LLVM", "Perl", "PyTorch", "TensorFlow", "Boost", "Intel MPI"]
+system_list = ["CharlieCloud", "LDMS", "Flux", "SICM", "AppSysFusion", "GMI", "Maestro/Merlin", "Splunk", "SLURM", "VmWare", "LSF"]
+visu_list = ["VTK/VTKm", "Paraview", "Visit", "Catalyst", "Conduit", "Cinema", "Ascent"]
+build_list = ["Spack", "BLT", "CMake", "Ninja", "Autoconf/Automake", "gdb", "git", "Gitlab", "git-lfs", "Valgrind", "AllineaForge", "TotalView", "Caliper", "Archer", "PAPI", "KokkosTools", "CDash", "STAT"]
+io_list = ["HDF5/Parallel-HDF5", "NetCDF, pNetCDF", "SEACAS", "UnifyFS", "ZFP", "HPSS, MarFS, SILO", "Exodus, yamlcpp", "GUFI, HIO, SCR, Sina/Kosh", "CGNS, libz", "DB2, Matio", "ADIOS, szip/AEC"]
+
+
+# Define the mapping from scale to numerical values
+scale_mapping = {
+    "Low": 0,
+    "Medium": 1,
+    "High": 2,
+    "Very High": 3
+}
+
+data_map = {
+    "solvers_list": (["KokkosKernels", "PETSc", "PARDISO", "Trilinos", "SuperLU-Dist", "STRUMPACK", "Hypre", "SPARSKIT", "BLAS", "SuperLU", "SparsePACK", "LAPACK"], "Solver Libraries"),
+    "math_list": (["SAMRAI", "STK", "MFEM", "UMR", "Portage", "Tangram", "Axom", "Overlink", "METIS", "ParMETIS", "Sculpt", "libigl"], "Math, Meshing, Discretization & Decomposition"),
+    "compilers_list": (["Kokkos", "RAJA Suite", "FleCSI", "Flang", "MPICH", "OpenMPI", "Legion", "PyKokkos", "KokkosRemoteMemorySpaces", "Fortran", "MPI", "C", "C++", "GCC", "HIP", "CUDA", "Python", "OpenMP", "Intel Compiler Suite", "LLVM", "Perl", "PyTorch", "TensorFlow", "Boost", "Intel MPI"], "Compilers, Runtimes and Languages"),
+    "system_list": (["CharlieCloud", "LDMS", "Flux", "SICM", "AppSysFusion", "GMI", "Maestro/Merlin", "Splunk", "SLURM", "VmWare", "LSF"], "System imaging, system monitoring and management"),
+    "visu_list": (["VTK/VTKm", "Paraview", "Visit", "Catalyst", "Conduit", "Cinema", "Ascent"], "Visualisation And Analysis"),
+    "build_list": (["Spack", "BLT", "CMake", "Ninja", "Autoconf/Automake", "gdb", "git", "Gitlab", "git-lfs", "Valgrind", "AllineaForge", "TotalView", "Caliper", "Archer", "PAPI", "KokkosTools", "CDash", "STAT"], "Build, Development and Software Eng."),
+    "io_list": (["HDF5/Parallel-HDF5", "NetCDF, pNetCDF", "SEACAS", "UnifyFS", "ZFP", "HPSS, MarFS, SILO", "Exodus, yamlcpp", "GUFI, HIO, SCR, Sina/Kosh", "CGNS, libz", "DB2, Matio", "ADIOS, szip/AEC"], "IO Storage/Data management")
+}
+
+for software_list, title in data_map.values():
+    print(f"Processing {title}: {software_list}")
+    average_value = dict()
+    # Define the reverse mapping
+    reverse_mapping = {v: k for k, v in scale_mapping.items()}
+
+    for software in software_list:
+        software_columns = [column for column in df.columns if software in column]
+        if software_columns:
+            # Apply the mapping to the specific columns
+            df[software_columns] = df[software_columns].replace(scale_mapping)
+            # Ignore rows with all NaN values
+            average_value[software] = df[software_columns].dropna(how='all').mean(axis=0)
+            # Convert the average value back to the scale
+            average_value[software] = average_value[software].round().map(reverse_mapping)
+            print(f"Average value for {software}: {average_value[software]}")
+            #print(f"Average value for {software}: {average_value[software]}")
+            # Print the results for each column
+            #for column in software_columns:
+            #    print(f"Results for {column}:")
+            #    print(df[column].map(reverse_mapping).dropna())
+        else:
+            print(f"No columns found for {software}")
+
+
+    # Define the table structure
+    table = {
+        ("Low", "Low"): [],
+        ("Low", "Medium"): [],
+        ("Low", "High"): [],
+        ("Low", "Very High"): [],
+        ("Medium", "Low"): [],
+        ("Medium", "Medium"): [],
+        ("Medium", "High"): [],
+        ("Medium", "Very High"): [],
+        ("High", "Low"): [],
+        ("High", "Medium"): [],
+        ("High", "High"): [],
+        ("High", "Very High"): [],
+        ("Very High", "Low"): [],
+        ("Very High", "Medium"): [],
+        ("Very High", "High"): [],
+        ("Very High", "Very High"): [],
+    }
+
+    # Fill the table with software names
+    for software in software_list:
+        row=dict()
+        col=dict()
+        ok=0
+        for key, val in average_value[software].items():
+            if "Likelihood" in key:
+                if val in ["Very High","High","Medium","Low"]:
+                    row[software]=val
+                else:
+                    row[software]="Low"
+            if "Impact" in key:
+                if val in ["Very High","High","Medium","Low"]:
+                    col[software]=val
+                else:
+                    col[software]="Low"
+        table[(row[software], col[software])].append(software)
+#    print(table)        
+
+    ## Create the AsciiDoc table
+    asciidoc_table = f"""
+.Likelihood-Impact Matrix for {title}
+|===\n|Likelihood \\ Impact|Very High|High|Medium|Low\n
+"""
+    #
+    for likelihood in ["Very High","High","Medium","Low"]:
+        asciidoc_table += f"|{likelihood}"
+        for impact in ["Very High","High","Medium","Low"]:
+            asciidoc_table += f"|{', '.join(table[(likelihood, impact)])}"
+        asciidoc_table += "\n"
+
+    asciidoc_table += "|===\n\n"
+
+    with open(f"doe-analysis.adoc", "a") as f:
+        f.write(f"== {title}")
+        f.write(asciidoc_table)
+
+
+

docs/software/analysis/doe-analysis.adoc

@@ -0,0 +1,77 @@
+== Solver Libraries
+.Likelihood-Impact Matrix for Solver Libraries
+|===
+|Likelihood \ Impact|Very High|High|Medium|Low
+
+|Very High||||
+|High||Hypre|Trilinos|
+|Medium||PETSc, STRUMPACK, SuperLU|PARDISO, SPARSKIT, SparsePACK|KokkosKernels
+|Low||BLAS, LAPACK|SuperLU-Dist|
+|===
+
+== Math, Meshing, Discretization & Decomposition
+.Likelihood-Impact Matrix for Math, Meshing, Discretization & Decomposition
+|===
+|Likelihood \ Impact|Very High|High|Medium|Low
+
+|Very High||||
+|High||MFEM||libigl
+|Medium||METIS, ParMETIS||
+|Low||SAMRAI||STK, UMR, Portage, Tangram, Axom, Overlink, Sculpt
+|===
+
+== Compilers, Runtimes and Languages
+.Likelihood-Impact Matrix for Compilers, Runtimes and Languages
+|===
+|Likelihood \ Impact|Very High|High|Medium|Low
+
+|Very High||||
+|High||PyKokkos, Python, TensorFlow||
+|Medium|C++, GCC|MPICH, OpenMPI, Fortran, MPI, HIP, CUDA, OpenMP, PyTorch, Boost, Intel MPI||Kokkos, C
+|Low|RAJA Suite|Flang, Intel Compiler Suite, LLVM|FleCSI, KokkosRemoteMemorySpaces, Perl|Legion
+|===
+
+== System imaging, system monitoring and management
+.Likelihood-Impact Matrix for System imaging, system monitoring and management
+|===
+|Likelihood \ Impact|Very High|High|Medium|Low
+
+|Very High||||
+|High|||CharlieCloud|
+|Medium||LSF||LDMS, Flux, SICM, AppSysFusion, GMI, Maestro/Merlin, Splunk, VmWare
+|Low||SLURM||
+|===
+
+== Visualisation And Analysis
+.Likelihood-Impact Matrix for Visualisation And Analysis
+|===
+|Likelihood \ Impact|Very High|High|Medium|Low
+
+|Very High||||
+|High||Visit, Conduit|Catalyst|Cinema, Ascent
+|Medium||VTK/VTKm, Paraview||
+|Low||||
+|===
+
+== Build, Development and Software Eng.
+.Likelihood-Impact Matrix for Build, Development and Software Eng.
+|===
+|Likelihood \ Impact|Very High|High|Medium|Low
+
+|Very High||||
+|High|git, git-lfs|Spack||
+|Medium|CMake, gdb|Autoconf/Automake, Gitlab, Valgrind, Caliper||Archer, PAPI, KokkosTools, CDash, STAT
+|Low|Ninja|BLT, TotalView|AllineaForge|
+|===
+
+== IO Storage/Data management
+.Likelihood-Impact Matrix for IO Storage/Data management
+|===
+|Likelihood \ Impact|Very High|High|Medium|Low
+
+|Very High||||
+|High||||
+|Medium|HDF5/Parallel-HDF5|NetCDF, pNetCDF, SEACAS, HPSS, MarFS, SILO, Exodus, yamlcpp, ADIOS, szip/AEC||UnifyFS, ZFP, GUFI, HIO, SCR, Sina/Kosh, CGNS, libz, DB2, Matio
+|Low||||
+|===
+

docs/software/analysis/exama-software-analysis.adoc

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+= PEPR NumPEx Exa-MA Software analysis
+Exa-MA
+v1.0 2023-05-31
+:toc: macro
+:doctype: book
+:title-page:
+:title-page-background-image: image:media/digital-background.png[]
+:title-page-background-color: #000000
+// :title-logo-image: image:media/logo-csmi.png[top=25%,align=center,pdfwidth=2in]
+:sectnums:
+:toc: left
+:toclevels: 2
+:icons: font
+:icon-set: fab
+
+[.metadata]
+{author} -- version {revnumber}, {revdate}
+
+== Introduction
+
+== Doe Software Analysis
+
+This section describes the software analysis for the DOE Stack for the Exa-MA project.
+
+include::doe-analysis.adoc[]

docs/software/analysis/ressources/themes/pdf-theme.yml

@@ -0,0 +1,51 @@
+extends: default
+title-page:
+  background-color: #666666
+  font-size: 18
+  font-color: '#000000'
+header:
+  height: 0.55in
+  line-height: 1
+  border_color: dddddd
+  border_width: 0.25
+  background-image: #image:../../media/logo-csmi.png[fit=scale-down,position=right]
+  recto:
+    center:
+      content: 'PEPR NumPEx - Exa-MA -- v{revnumber}, {docdate}'
+  verso:
+    center:
+      content: $header-recto-center-content
+footer:
+#  background-image: image:../../media/logo-csmi.png[width=0.5in] image:../../media/logo-unistra.png[width=0.5in]
+  background-image: #image:../../media/logo-unistra.png[fit=scale-down,position=right]
+  height: 0.65in
+  line-height: 1
+  recto:
+    left:
+      content: '{section-or-chapter-title} | {page-number} of {page-count}'
+  verso:
+    left:
+      content: '{page-number} of {page-count} | *{chapter-title}*'
+
+font:
+  catalog:
+    merge: true
+    UnistraA:
+      normal: UnistraA-Regular.ttf
+      bold: UnistraA-Bold.ttf
+      italic: UnistraA-Italic.ttf
+      bold_italic: UnistraA-BoldItalic.ttf    
+    UnistraB:
+      normal: UnistraB-Regular.ttf
+      bold: UnistraB-Bold.ttf
+      italic: UnistraB-Italic.ttf
+      bold_italic: UnistraB-BoldItalic.ttf
+
+heading:
+  font-family: UnistraB
+  font-style: bold
+#base:
+#  font-family: UnistraB
+#  font-style: normal
+h2:
+  font-color: '#da3131'