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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.08845 |
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| _version_ | 1866915997489823744 |
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| author | Cezar, Toma-Stefan Maroudas, Marios Horns, Dieter |
| author_facet | Cezar, Toma-Stefan Maroudas, Marios Horns, Dieter |
| contents | High-throughput physics experiments require efficient and increasingly complex real-time processing. This paper presents a modular, software-defined platform combining high-bandwidth PCIe digitizers with consumer GPUs to achieve continuous, zero-dead-time data acquisition. Utilizing NVIDIA CUDA, the system provides a scalable pipeline for real-time fast Fourier transforms and statistical averaging. Benchmarks demonstrate that the platform can sustain continuous processing at sampling rates up to 500 MSa/s, effectively managing data throughputs of 1 GB/s. To validate the in-situ zero-dead-time architecture, end-to-end phase continuity tests were conducted, constraining fractional data loss to below $10^{-12}$. Furthermore, long-term system stability was demonstrated through an uninterrupted one-month data acquisition run. In its current deployment for the WISPLC dark matter experiment, the platform operates at 124 MSa/s with a resolution bandwidth of 0.1 Hz. This implementation enabled a significant reduction in data storage requirements using real-time spectral averaging. The callback-driven software architecture, multi-GPU workload distribution, and custom hardware shielding solutions are detailed, establishing this platform as a flexible and cost-effective alternative to traditional hardware-based pipelines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_08845 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Modular Zero-Dead-Time Data Acquisition and Real-Time GPU Processing Platform for High Throughput Physics Experiments Cezar, Toma-Stefan Maroudas, Marios Horns, Dieter Instrumentation and Detectors High Energy Physics - Experiment High-throughput physics experiments require efficient and increasingly complex real-time processing. This paper presents a modular, software-defined platform combining high-bandwidth PCIe digitizers with consumer GPUs to achieve continuous, zero-dead-time data acquisition. Utilizing NVIDIA CUDA, the system provides a scalable pipeline for real-time fast Fourier transforms and statistical averaging. Benchmarks demonstrate that the platform can sustain continuous processing at sampling rates up to 500 MSa/s, effectively managing data throughputs of 1 GB/s. To validate the in-situ zero-dead-time architecture, end-to-end phase continuity tests were conducted, constraining fractional data loss to below $10^{-12}$. Furthermore, long-term system stability was demonstrated through an uninterrupted one-month data acquisition run. In its current deployment for the WISPLC dark matter experiment, the platform operates at 124 MSa/s with a resolution bandwidth of 0.1 Hz. This implementation enabled a significant reduction in data storage requirements using real-time spectral averaging. The callback-driven software architecture, multi-GPU workload distribution, and custom hardware shielding solutions are detailed, establishing this platform as a flexible and cost-effective alternative to traditional hardware-based pipelines. |
| title | A Modular Zero-Dead-Time Data Acquisition and Real-Time GPU Processing Platform for High Throughput Physics Experiments |
| topic | Instrumentation and Detectors High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2605.08845 |