Processamento multicore para reconstrução online de energia por meio de redes neurais

Melissa Santos Aguiar, Lucca Viccini, Dabson Ferreira, Mariana Resende, Mateus Faria, Luciano Filho, José de Seixas

DOI: 10.14209/SBRT.2020.1570661648

Evento: XXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2020)

Keywords: Calorimetria Rede neural FPGA Multicore

Abstract

Energy reconstruction in Calorimeters is a process executed in pulses generated in its electrodes to estimate the energy of subatomic particles that go through its material. Non-Gaussian characteristics of the noise in calorimeters operating at high frame rates demonstrate that non-linear estimation methods are more appropriate. Nevertheless, such methods tend to have a high computational cost, which makes their online implementation an inconvenience. Is presented with this work, the implementation of an embedded neural network in a multicore process in FPGA, capable of operating at an acquisition rate above 40 MHz, as well as an implementation in the Calorimeter of the ATLAS Experiment.

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