Add multithreading to CbmTaskUnpack and fix compiler errors on several systems

This MR adds simple multithreading to CbmTaskUnpack. It is meant as a starting point in this direction and to allow us to gain relevant experience.

A significant performance improvement is achieved by using std::sort with the std::execution::par_unseq parameter when time-sorting all digis in the end.

In addition, the components are processed in parallel, yielding another improvement. Here, the performance gains appear to be limited by the process of adding all digis to a common vector.

Further parallelization inside the components (i.e., on microslice level) is not yet attempted in this MR.

On the mFLES login node, the Unpack tasks runs at about 300 MB/s for our benchmark file.

bin/cbmreco_fairrun -i ~/tmp/1588_node8_1_0000.tsa -c ../reco/tasks/CbmRecoConfigExample.yaml

reco/tasks/CMakeLists.txt

@@ -2,7 +2,6 @@
 # V. Friese,     2 June 2021
 
 
-
 # -----   Library name   ----------------------------------
 Set(LIBRARY_NAME CbmRecoTasks)
 # ---------------------------------------------------------
@@ -70,6 +69,10 @@ CbmData
 Algo
 external::yaml-cpp
 )
+if(OpenMP_CXX_FOUND)
+  list(APPEND DEPENDENCIES OpenMP::OpenMP_CXX)
+endif()
+
 # ---------------------------------------------------------
 
 
@@ -77,6 +80,25 @@ external::yaml-cpp
 set(LINKDEF ${LIBRARY_NAME}LinkDef.h)
 # ---------------------------------------------------------
 
+# Check if the compiler supports std::execution in the respective STL
+# library
+CHECK_CXX_SOURCE_COMPILES("
+#include <numeric>
+#include <vector>
+#include <execution>
+
+int main(int argc, char *argv[])
+{
+    std::vector<double> v(10, 1);
+
+    auto result = std::reduce(std::execution::par, v.begin(), v.end());
+    return 0;
+}" HAS_STD_EXECUTION)
+
+if (HAS_STD_EXECUTION)
+  message("Execution is available in STL")
+  add_definitions(-DWITH_EXECUTION)
+endif()
 
 # -----  Let cmake do the job   ---------------------------
 include_directories( ${INCLUDE_DIRECTORIES})