Speaker
Description
Modern scientific experiments often generate large amounts of data, posing challenges for real-time
processing and analysis. ASAPO, a high-performance streaming framework developed at DESY,
addresses these challenges by providing a robust solution for online and offline data processing.
Leveraging TCP/IP and RDMA over Ethernet and Infiniband, ASAPO facilitates high-bandwidth
communication between detectors, storage systems, and analysis processes.
ASAPO offers user-friendly interfaces for C/C++ and Python on all major platforms, streamlining the
development of data processing pipelines. A high-level Python library reduces boilerplate code and
enables the creation of complex analysis workflows with ease. Key features include automatic
retransfer, trivial parallelization on a per-image basis, support for multi-module detectors, and webbased
monitoring capabilities.
Several experimental facilities at Petra III already benefit from ASAPO, employing it in various dataprocessing
pipelines. Examples include azimuthal integration of X-ray scattering data, peak finding,
and indexing of diffraction patterns. These applications demonstrate ASAPO's versatility and
effectiveness in accelerating scientific discovery.
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