The development of a general purpose ARM-based processing unit for the ATLAS TileCal sROD

Abstract

The Large Hadron Collider at CERN generates enormous amounts of raw data which present a serious computing challenge. After Phase-II upgrades in 2022, the data output from the ATLAS Tile Calorimeter will increase by 200 times to 41 Tb/s! ARM processors are common in mobile devices due to their low cost, low energy consumption and high performance. It is proposed that a cost-effective, high data throughput Processing Unit (PU) can be developed by using several consumer ARM processors in a cluster configuration to allow aggregated processing performance and data throughput while maintaining minimal software design difficulty for the end-user. This PU could be used for a variety of high-level functions on the high-throughput raw data such as spectral analysis and histograms to detect possible issues in the detector at a low level. High-throughput I/O interfaces are not typical in consumer ARM System on Chips but high data throughput capabilities are feasible via the novel use of PCI-Express as the I/O interface to the ARM processors. An overview of the PU is given and the results for performance and throughput testing of four different ARM Cortex System on Chips are presented.

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

“…Currently Optimal Filtering is used for signal processing of the raw data, but more sophisticated algorithms may be required in future [5,7]. A general purpose co-processor is able to run more sophisticated and memory intensive algorithms than an FPGA-based device, although the latency cannot be controlled like it can with an FPGA, which is why the sROD is used in the data path [6].…”