Speaker
Description
As experiment data volumes in Nuclear Physics continue to rise – by some estimates up to 3 orders of magnitude this decade - the development of data streaming and data management capabilities has taken on new importance. Traditionally Data Acquisition (DAQ) readout has been facilitated through software embedded in the instrument or direct register readout via bus systems such the Versa Module Eurocard (VME) architecture. Recently, DAQs in Nu-clear Physics have begun implementing streaming readout in which digitizer instrumentation sends data over the network to data management computing clusters for processing and storage.
This paradigm shift now means that DAQ network infrastructure and data management systems have become a criti-cal link in the next generation of scientific instruments. Both the choice of network hardware and its topology influ-ence data rates and tolerance for failures. Software tools such as iperf3 and TRex are often used to evaluate these networks. While they provide configurable traffic generation, these tools require extensive configuration to emu-late real multi-channel correlated DAQ streams. They can also lack the timing precision native to ASIC or FPGA-based systems used in real-time DAQs.
To address these issues, we present “Solidago” - an FPGA-based streaming DAQ emulator capable of streaming 160 Gbps of synthetic digitizer events with the same timing characteristics of a clock-synchronized digitizer array. We characterize Solidago’s streaming capabilities and compare it to real streaming digitizers and current software emu-lation tools. We further demonstrate the practical application of Solidago to stress-test and tune DAQ networks and data management systems.
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| IEEE Member | No |
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