  Today the LHC offline computing relies heavily on CPU resources, despite the
interest in compute accelerators, such as GPUs, for the longer term future. The
number of cores per CPU socket has continued to increase steadily, reaching the
levels of 64 cores (128 threads) with recent AMD EPYC processors, and 128 cores
on Ampere Altra Max ARM processors. Over the course of the past decade, the CMS
data processing framework, CMSSW, has been transformed from a single-threaded
framework into a highly concurrent one. The first multithreaded version was
brought into production by the start of the LHC Run 2 in 2015. Since then, the
framework's threading efficiency has gradually been improved by adding more
levels of concurrency and reducing the amount of serial code paths. The latest
addition was support for concurrent Runs. In this work we review the
concurrency model of the CMSSW, and measure its scalability with real CMS
applications, such as simulation and reconstruction, on mode rn many-core
machines. We show metrics such as event processing throughput and application
memory usage with and without the contribution of I/O, as I/O has been the
major scaling limitation for the CMS applications.
