Speaker
Description
This contribution presents Track Lab, a multi-platform DAQ software for solid-state pixel detectors designed with versatility and high-performance applications in mind. Originally designed to service the Timepix3 ASIC [1] and the Katherine readout [2], Track Lab has outgrown
its intended application and gained compatibility with a diverse range of research instruments. One of its pivotal features is the capability to perform online analysis by composing complex data workflows from simple building blocks, such as filters, transformations or aggregations. Inspired by large-scale systems like MapReduce and Hadoop [3], Track Lab allows for an arbitrary number of processing elements to be visually linked together in user interface to form directed acyclic graphs (DAG), which are typically terminated in persistent storage or real-time plots
that conveniently generate immediate feedback for the user. For extensibility, logic of these
elements is implemented in plug-in modules, which are included with the software. While the
latest program version ships 14 such modules, their programming interface is publicly docu-
mented, so as to allow custom plug-ins and extensions to be developed easily.
Track Lab utilizes many conventional strategies to resolve a commonly encountered trade-
off between high performance and extensibility. First of all, thanks to multi-threading, its data
processing elements operate simultaneously in parallel, enabling them to fully utilize advantages
of many-core CPUs. Secondly, data flow is handled by ZeroMQ [4], an industry-standard
message-passing middleware, which significantly reduces memory footprint of the program by
transparently multiplexing data between a single sender and multiple receivers. Broad adoption
of ZeroMQ also permits nearly effortless interoperability with data sources and sinks provided by
external programs. Finally, high throughput is achieved by employing asynchronous memory-
mapped file access, and wide-bandwidth system buses.
While Track Lab’s development is continuously ongoing, its stable versions have been thus
far successfully deployed in Mini.PAN [5] beam campaigns at SPS, nuclear safety applications [6]
and at the ATLAS-TPX3 [7] and MoEDAL-TPX3 [8] detector networks at LHC. Thanks to such
a wide range of applications, its compatibility has been verified for all three major operating
systems: Linux, Windows and macOS. Binaries of the software can be freely used by the public,
and its sources are available upon request.
| Type of presentation (in-person/online) | online presentation (zoom) |
|---|---|
| Type of presentation (scientific results or project proposal) | Presentation on scientific results |
