Editing Portal:HPC - High Performance Computing (section)

=== PDL parallel CPU support ===

PDL also has built-in support for parallel CPU execution. The `PDL::ParallelCPU` documentation says PDL can split numerical processing across multiple processor threads, or pthreads, using functions such as `set_autopthread_targ` and `set_autopthread_size`. The documentation notes that this can improve processing performance by greater than 2–4× in many cases on multi-core or multi-processor machines.<ref>MetaCPAN, “PDL::ParallelCPU,” https://metacpan.org/pod/PDL%3A%3AParallelCPU, accessed July 3, 2026.</ref>

This is significant because modern compute nodes are multi-core. A Perl/PDL program that operates on large arrays can sometimes benefit from parallel execution inside PDL without the programmer manually writing threads around every loop.

PDL’s parallel CPU model is not the same thing as MPI across a cluster. It is primarily a shared-memory, single-node technique. It is useful when the data fits within one node’s memory and the computation can be divided across cores.