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May 8 – 12, 2023
Norfolk Waterside Marriott
US/Eastern timezone

A fast and optimized data-acquisition and control software for the Timepix4 ASIC

Not scheduled
1h
Hampton Roads Ballroom and Foyer Area (Norfolk Waterside Marriott)

Hampton Roads Ballroom and Foyer Area

Norfolk Waterside Marriott

235 East Main Street Norfolk, VA 23510
Poster Poster Poster Session

Speaker

Cavallini, Viola (INFN and University of Ferrara)

Description

Timepix4 is a hybrid pixel detector readout ASIC developed by the Medipix4 Collaboration. It consists of a matrix of about 230 k pixels with 55 micron pitch, equipped with amplifier, discriminator and time-to-digital converter with 195 ps bin size that allows to measure time-of-arrival and time-over-threshold. It is equipped with two different types of links: slow control links, for the configuration and the slow readout (up to 1 Gbps) of the output data, and fast links, based on 16 serial links with a speed of up to 10 Gbps each.
An innovative ASIC like Timepix4 must have a strong software counterpart, capable of an optimal management of the hardware system, efficient in its configuration, optimized for the fast readout and easy to operate for the final user, expert or not.
We present a new ad-hoc software for this purpose, based on the Timepix4 data acquisition architecture, entirely open-source, extremely flexible thanks to the C++ low-level classes and user-friendly. The software is organized in a structure of classes that allow to configure both the Control Board and the Timepix4 ASIC and to handle the slow and fast readout. Moreover, the storage, the post-acquisition analysis and every other custom class can be easily added without modifying the basic organization of the software.
One of the main features of this software is the compatibility with different hardware setups that make use of Timepix4, independently from the specific Control Board adopted: changing only a few low-level functions, the ones strictly correlated to the communication protocol, all the higher-level classes will work correctly.
The high-rate readout will be our next challenge, implementing a class capable of reading and storing correctly every packet, up to a maximum rate of 160 Gbps.

Consider for long presentation No

Primary authors

Cavallini, Viola (INFN and University of Ferrara) Dr Biesuz, Nicolò Vladi (INFN) Mr Bolzonella, Riccardo (INFN and University of Ferrara) Dr Cotta Ramusino, Angelo (INFN) Prof. Fiorini, Massimiliano (INFN and University of Ferrara) Dr Gianoli, Alberto (INFN) Dr Guarise, Marco (INFN and University of Ferrara) Dr Llopart Cudie, Xavier (CERN) Prof. Schifano, Sebastiano Fabio (INFN and University of Ferrara)

Presentation materials