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Analyzing the increasingly large volumes of data that are available today, possibly including the application of custom machine learning models, requires the utilization of distributed frameworks. This can result in serious productivity…
An extensible, component-based framework has been developed at Fermilab to promote software reuse and provide a common platform for developing a family of test and data analysis systems. The framework allows for configuring applications…
This paper presents the design criteria and the current implementation of a generic and functionally rich data acquisition framework for high performance detectors called RASHPA. The framework is based on the use of RDMA mechanisms for…
With the increasing physical event rate and number of electronic channels, traditional readout scheme meets the challenge of improving readout speed caused by the limited bandwidth of crate backplane. In this paper, a high-speed data…
We have developed a novel data acquisition system for measuring tracking parameters of a silicon detector in a particle beam. The system is based on a commercial Analog-to-Digital VME module and a PC Linux based Data Acquisition System.…
The data acquisition software framework, EUDAQ, was originally developed to read out data from the EUDET-type pixel telescopes. This was successfully used in many test beam campaigns in which an external position and time reference were…
A noise-tolerant data communications fabric has been developed to meet the real-time data acquisition and control requirements of fast feedback loops, machine protection systems, pulse-to-pulse sequencing, and machine-experiment…
We implemented a real-time data processor (rta-dp) framework that can be used to develop real-time analysis pipelines and data handling systems to manage high-throughput data streams with distributed applications in the context of ground…
In the last three years, the architecture of Frascati Tokamak Upgrade (FTU) experimental database has undergone meaningful modifications, data and codes have been moved from mainframe to UNIX platforms and AFS (Andrew File System) has been…
The video acquisition and processing systems are commonly used in industrial and scientific applications. Many of them utilize Camera Link interface for the transmission of a video stream from the camera to the host system. The framework…
In this work, we develop DeepWiPHY, a deep learning-based architecture to replace the channel estimation, common phase error (CPE) correction, sampling rate offset (SRO) correction, and equalization modules of IEEE 802.11ax based orthogonal…
Next generation high-performance RDMA-capable networks will require a fundamental rethinking of the design and architecture of modern distributed DBMSs. These systems are commonly designed and optimized under the assumption that the network…
The data acquisition system (DAQ) of the future Cherenkov Telescope Array (CTA) must be ef- ficient, modular and robust to be able to cope with the very large data rate of up to 550 Gbps coming from many telescopes with different…
A new generation of radio telescopes is achieving unprecedented levels of sensitivity and resolution, as well as increased agility and field-of-view, by employing high-performance digital signal processing hardware to phase and correlate…
As modern AI workloads increasingly rely on heterogeneous accelerators, ensuring high-bandwidth and layout-flexible data movements between accelerator memories has become a pressing challenge. Direct Memory Access (DMA) engines promise high…
Data Acquisition and Control Systems used in high energy physics experiments, such as those which will take place in the Large Hadron Collider (LHC) at CERN, require the specification of data formats and transmission protocols as well as…
In this paper, we describe a modular data acquisition system developed as the foundation of a cosmic ray detector network. Each detector setup (henceforth referred as a station) is composed of an independent hardware device that can be…
The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and…
The optimization of an accelerator relies on the ability to monitor the behavior of the beam in an intelligent and timely fashion. The use of processor-driven front-ends allowed for the deployment of smart systems in the field for improved…
Modern software engineering of electronic structure codes has seen a paradigm shift from monolithic workflows towards object-based modularity. Software objectivity allows for greater flexibility in the application of electronic structure…