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When processing large amounts of data, the rate at which reading and writingcan take place is a critical factor. High energy physics data processingrelying on ROOT is no exception. The recent parallelisation of LHC experiments'software frameworks and the analysis of the ever increasing amount of collisiondata collected by experiments further emphasized this issue underlying the needof increasing the implicit parallelism expressed within the ROOT I/O. In thiscontribution we highlight the improvements of the ROOT I/O subsystem whichtargeted a satisfactory scaling behaviour in a multithreaded context. Theeffect of parallelism on the individual steps which are chained by ROOT to readand write data, namely (de)compression, (de)serialisation, access to storagebackend, are discussed. Performance measurements are discussed through reallife examples coming from CMS production workflows on traditional serverplatforms and highly parallel architectures such as Intel Xeon Phi.

Increasing Parallelism in the ROOT I/O Subsystem