Scalable data concentrator with baseline interconnection network for triggerless data acquisition systems

TL;DR

This paper introduces a scalable, high-speed data concentrator using the Baseline Network with Reversed Outputs (BNRO) for triggerless DAQ systems, enhancing scalability and efficiency in data routing and processing.

Contribution

The paper presents a novel BNRO-based data concentrator architecture that improves scalability and resource efficiency for triggerless DAQ systems.

Findings

Successfully simulated 4 and 5 layer networks (16 and 32 inputs)

Implemented and tested FPGA prototype for 16 inputs

Enhanced scalability with added network layers and pipeline registers

Abstract

Triggerless Data Acquisition Systems (DAQs) require transmitting the data stream from multiple links to the processing node. The short input data words must be concentrated and packed into the longer bit vectors the output interface (e.g., PCI Express) uses. In that process, the unneeded data must be eliminated, and a dense stream of useful DAQ data must be created. Additionally, the time order of the data should be preserved. This paper presents a new solution using the Baseline Network with Reversed Outputs (BNRO) for high-speed data routing. A thorough analysis of the network's operation enabled increased scalability compared to the previously published concentrator based on an 8x8 network. The solution may be scaled by adding additional layers to the BNRO network while minimizing resource consumption. Simulations were done for 4 and 5 layers (16 and 32 inputs). The FPGA implementation and tests in the actual hardware have been successfully performed for 16 inputs. The pipeline registers may be added in each layer independently, shortening the critical path and increasing the maximum acceptable clock frequency.