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

被引：0
|
作者：
Cox, Mitchell A. [1 ]
机构：
[1] Univ Witwatersrand, Sch Phys, ZA-2050 Johannesburg, South Africa
来源：
HIGH ENERGY PARTICLE PHYSICS WORKSHOP (HEPPW2015) | 2015年 / 645卷
关键词：
D O I：
10.1088/1742-6596/645/1/012018
中图分类号：
O412 [相对论、场论]; O572.2 [粒子物理学];
学科分类号：
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.
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页数：5
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