Towards Optimal Filtering on ARM for ATLAS Tile Calorimeter Front-End Processing

High Energy Particle Physics Workshop 2015

Cox, Mitchell A.^1

School of Physics, University of the Witwatersrand, Johannesburg

2050, South Africa^1

关键词: Cluster configurations;    Energy reconstruction;    Field programmable gate array (FPGAs);    Front-end processing;    High level algorithms;    Large Hadron Collider;    Processing performance;    Tile calorimeters;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/645/1/012018/pdf
DOI  :  10.1088/1742-6596/645/1/012018

来源: IOP

【 摘 要 】

The Large Hadron Collider at CERN generates enormous amounts of raw data which presents a serious computing challenge. After planned upgrades in 2022, the data output from the ATLAS Tile Calorimeter will increase by 200 times to over 40 Tb/s. Advanced and characteristically expensive Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAS) are currently used to process this quantity of data. It is proposed that a cost- effective, high data throughput Processing Unit (PU) can be developed by using several ARM System on Chips in a cluster configuration to allow aggregated processing performance and data throughput while maintaining minimal software design difficulty for the end-user. ARM is a cost effective and energy efficient alternative CPU architecture to the long established x86 architecture. This PU could be used for a variety of high-level algorithms on the high data throughput raw data. An Optimal Filtering algorithm has been implemented in C++ and several ARM platforms have been tested. Optimal Filtering is currently used in the ATLAS Tile Calorimeter front-end for basic energy reconstruction and is currently implemented on DSPs.