A generic streaming data acquisition system for high-energy physics experiments

Abstract

The data acquisition system is a vital component in the high-energy physics experiment. To reduce redundant developments and allow for a fast setup under changing conditions, D-Matrix has been developed as an integrative solution in digital signal domain, including the hardware infrastructure and the data handling logical system. Its philosophy is to abstract different tasks in the data processing and encapsulate them as reusable modules with standard inter-module connectors. Furthermore, D-Matrix builds a unified model to integrate software and hardware design so that the system can be built from a global view. D-Matrix will be used in ion cooler-storage-ring external-target experiments. It aims at the research of phase structure of cold and high baryon density nuclear matter and the equation of states of cold asymmetric nuclear matter at supra-saturation densities. This DAQ can also be used in other high-energy physics experiments with little modifications. This paper presents the architecture and some details of the D-Matrix.

A generic node identification and routing algorithm in a distributed data acquisition platform: D-Matrix

“…D-Matrix abstracts various information transmissions and processing in the DAQ into different streams. In order to address the challenges of transmitting multiple streams over the same physical interface and encapsulating different physical layer interfaces into a common application layer interface, D-Matrix introduces a Multiple Point-to-Point transmission model [13], referred to as the MPP model (figure 1). The MPP model encapsulates based on the OSI model, abstracting the transmission of multiple streams through a physical interface into multiple point-to-point stream interfaces.…”

“…Based on the encapsulation of the OSI model, D-Matrix introduces a Multiple Point-to-Point (MPP) transmission model [13]1 that abstracts distinct information transmission channels within a single physical interface. Leveraging the MPP model, communication tasks such as node identification can share the same link with data transmission, enabling the utilization of identical stream processing modules to achieve desired functionalities across various connection methods.…”