The major upgrade of the BM@N experiment for the heavy ion program is a new hybrid tracking system. It consists of seven planes of GEM detectors and four silicon tracking stations based on the modules with double-sided microstrip silicon sensors of CBM type. The BM@N silicon tracking system (STS) will conceptually inherit the data acquisition system (DAQ) from the CBM silicon tracker currently in development for FAIR. This is an entirely data driven acquisition system relying on purely self-triggering readout channels, which will also be adopted for the operation with BM@N trigger. The core components of the readout chain are front-end boards (FEB), GBTxEmu board and GBTxEmu readout interface (GERI) board. The front-end board is an integrated part of the STS module. The main components of FEB are eight STS-XYTER ASICs which are needed for the readout of one side of the silicon sensor. The GBTxEmu board comprises an FPGA which emulates functionality of the CERN GBTx ASIC and provides a bidirectional optical link between front-end electronics and data processing boards in the computer nodes. The GERI board implements the following functionalities: concentrating and preprocessing of the data stream, filtering of the data according to the BM@N trigger signals and providing an interface for the detector control system (DCS) to configure readout electronics.

Fast Data-Driven Readout System for the Wide Aperture Silicon Tracking System of the BM@N Experiment

An experimental setup for quality assurance of the BM@N experiment tracking modules based on pulsed diode lasers is described. The main idea of the setup is to simulate an ionizing particle traversing a silicon sensor of the module. The tracking modules are based on silicon microstrip sensors and readout electronics STS-XYTER ASICs. Diode lasers with wavelengths of 635 and 1064 nm are used in the setup. The lasers are powered by a pulse oscillator which can generate rectangular pulses with high frequency. Laser radiation is transmitted through a single-mode optical fiber and an attenuator to a focuser and then is focused on a tracking module sensor. After that, the module is moved along with a positioning table in order to measure signals from all strips and readout channels.

Laser Setup for Quality Assurance of the BM@N Silicon Tracking Modules

Modern DAQ systems typically use the FPGA-based PCIe cards to concentrate and deliver the data to a computer used as an entry node of the data processing network. This paper presents a QEMU-based methodology for the co-development of the FPGA-based hardware part, the Linux kernel driver, and the data receiving application. That approach enables quick verification of the FPGA firmware architecture, organization of control registers, the functionality of the driver, and the user-space application. The developed design may be tested in different emulated architectures with a changeable CPU, IOMMU, size of memory, and the number of DAQ cards.

QEMU-based hardware/software co-development for DAQ systems

Modern DAQ systems typically use the FPGA-based PCIe cards to concentrate and deliver the data to a computer used as an entry node of the data processing network. This paper presents a QEMU-based methodology for the co-development of the FPGA-based hardware part, the Linux kernel driver, and the data receiving application. This approach enables quick verification of the FPGA firmware architecture, organization of control registers, the functionality of the driver, and the user-space application. The developed design may be tested in different emulated architectures with a changeable CPU, IOMMU, size of memory, and the number of DAQ cards. 

/pdf/qemu-based-hardware-software-co-development-for-daq-systems-3q7edevb.pdf

In recent years, experiments in particle physics and nuclear physics have required faster data collection systems and advanced trigger systems, as the beam intensity has been increased. The current data acquisition (DAQ) system at the Japan Proton Accelerator Research Complex (J-PARC) Hadron Experimental Facility (HEF) uses fixed- and low-latency triggers with dedicated hardware to reduce data and event-building software that merges data into a single endpoint. This conventional DAQ system is expected to be inadequate for future experiments. It has to be replaced with a new simplified but powerful system called streaming DAQ, which collects the detector signals and filters them with software running on many computers. Therefore, we developed a prototype of streaming DAQ software for the J-PARC HEF using FairMQ and Redis as middleware. The key features include simplicity and a low learning cost to develop and be operated by a small number of people. The software can be used in a fully streaming readout system and in the triggered DAQ and the combined DAQ of the hardware and software triggers.

M. Shitenkow

Papers

Fast Data-Driven Readout System for the Wide Aperture Silicon Tracking System of the BM@N Experiment

The Silicon Tracking System as a Part of Hybrid Tracker of BM@N Experiment

The Silicon Tracking System as a Part of Hybrid Tracker of BM@N Experiment