In a nutshell¶
What is PARAPROBE?¶
What are the user benefits?¶
Which parallelization concepts are employed?¶
Process data parallelism via the Message Passing Interface (MPI_) API PARAPROBE processes each individual measurement through a single process. This enables to either distribute parameter sweeping studies of the same tip on practically hundred thousands of processes or to process trivially in parallel multiple tips using the same automatized analysis protocol. At runtime, MPI invokes library calls to communicate pieces of information between physically disjoint computers if necessary. As MPI is a library, it requires installation and linking.
Shared memory thread data parallelism via the Open Multi-Processing (OpenMP_) API. PARAPROBE partitions the point data of each measurement into spatially disjoint chunks. Explicit strategies are applied to map and place the data chunks in thread-local memory to reduce false sharing and performance degradation on resources with multiple ccNUMA layers. OpenMP builds on preprocessor directives through which the corresponding pragmas are translated during compilation. As such, OpenMP needs no installation.