ASTROFLOW: A Real-time End-to-end Pipeline for Radio Single-pulse Searches

Abstract Fast radio bursts (FRBs) are extremely bright, millisecond-duration cosmic transients of unknown origin. The growing number of wide-field and high-time-resolution radio surveys, particularly with next-generation facilities such as the Square Kilometre Array and MeerKAT, will dramatically increase FRB discovery rates, but will also produce data volumes that overwhelm conventional search pipelines. Real-time detection thus demands software that is both algorithmically robust and computationally efficient. We present A stroflow , an end-to-end, GPU-accelerated pipeline for single-pulse detection in radio time–frequency data. Built on a unified C++/CUDA core with a Python interface, A stroflow integrates radio-frequency interference excision, incoherent dedispersion, dynamic-spectrum tiling, and a YOLO-based deep detector. Through vectorized memory access, shared-memory tiling, and OpenMP parallelism, it achieves >10× faster-than-real-time processing on consumer GPUs for a typical 150 s, 2048-channel observation—while preserving high sensitivity across a wide range of pulse widths and dispersion measures. These results establish the feasibility of a fully integrated, GPU-accelerated single-pulse search stack, capable of scaling to the data volumes expected from upcoming large-scale surveys. A stroflow offers a reusable and deployable solution for real-time transient discovery, and provides a framework that can be continuously refined with new data and models.