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ATLAS FTK challenge: simulation of a billion-fold hardware parallelism

During the current LHC shutdown period the ATLAS experiment will upgrade the Trigger and Data Acquisition system to include a hardware tracker coprocessor: the Fast Tracker (FTK). The FTK accesses the 80 million of channels of the ATLAS silicon detector, identifying charged tracks and reconstructing...

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Detalles Bibliográficos
Autor principal: Vaniachine, A
Lenguaje:eng
Publicado: 2014
Materias:
Acceso en línea:http://cds.cern.ch/record/1752592
Descripción
Sumario:During the current LHC shutdown period the ATLAS experiment will upgrade the Trigger and Data Acquisition system to include a hardware tracker coprocessor: the Fast Tracker (FTK). The FTK accesses the 80 million of channels of the ATLAS silicon detector, identifying charged tracks and reconstructing their parameters in the entire detector at a rate of up to 100 KHz and within 100 microseconds. To achieve this performance the FTK system utilizes the computing power of a custom ASIC chip with associative memory (AM) designed to perform “pattern matching” at very high speed, and the track parameters are calculated using modern FPGAs. To control this massive system a detailed simulation has been developed with the goal of supporting the hardware design and studying the impact of such a system in the ATLAS online event selection at high LHC luminosities. The two targets, electronic design and physics performance evaluation, have different requirements: while the hardware design requires accurate emulation of a relatively small data sample, physics studies require millions of events and the efficient use of CPU is important. We present the issues related to emulating this system on a commercial CPU platform, using ATLAS computing Grid resources, and the solutions developed in order to mitigate these problems to allow the emulation to perform the studies required to support the system design, construction and installation.