Mr Andrei Gheata (CERN/ISS)
ALICE offline group has developed a set of tools that do formalize data access patterns and impose certain rules on how individual data analysis modules have to be structured in order to maximize the data processing efficiency at the whole collaboration scale. The ALICE analysis framework was developed and extensively tested on MC reconstructed data during the last 2 years in the ALICE distributed computing environment. The talk will describe the architecture of the framework and its main features making it a success among ALICE users: transparent usage of the computing infrastructure (PROOF, GRID), data access performance for several concurrent tasks and simplicity to use. We will also focus on the experience and results accumulated during this period, discussing pros and cons of this unifying approach at data analysis level.
On behalf of the ALICE Core Offline
|Presentation type (oral | poster)||oral|