Radio telescopes typically use large steel dishes to point at and observe radio sources. The LOFAR radio telescope is different, and uses tens of thousands of fixed antennas instead, a novel design which allows many ground-breaking features for radio astronomy. One such a feature is the fact that LOFAR observes omnidirectionally, and focusses by accumulating the signals of its antennas in software in real time. In fact, the parallel processing power and high-speed interconnect in our supercomputer allows us to look at hundreds of sources at the same time. The power to observe many sources in parallel serves a broad range of scientific astronomical interests, and creates novel opportunities for performing astronomical observations.
Radio telescopes typically use large steel dishes to point at and observe radio sources. The LOFAR radio telescope is different, and uses tens of thousands of fixed antennas instead, a novel design which allows many ground-breaking features for radio astronomy. One such a feature is the fact that LOFAR observes omnidirectionally, and focusses by accumulating the signals of its antennas in software in real time. In fact, the parallel processing power and high-speed interconnect in our supercomputer allows us to look at hundreds of sources at the same time.% The power to observe many sources in parallel serves a broad range of scientific astronomical interests.
LOFAR is also the first major telescope to process its data in software, instead of needing a dedicated hardware design. By using software, the processing remains flexible and scalable, and new features are easier to implement and to maintain. It is through the use of software that we can fully explore the novel features and the power of our unique instrument.
In this paper, we present the processing pipeline in our supercomputer which enables our parallel observations. Our so-called \emph{Pulsar Pipeline} is implemented on a supercomputer, and receives up to 64 data streams from the stations at 3.1 Gb/s each. Inside the supercomputer, signal-processing techniques, weighted addition, and two all-to-all exchanges are performed. Our pulsar pipeline further expresses the power of a software telescope implemented using parallel processing techniques. We present the trade-offs in our design, the CPU and I/O performance bottlenecks that we encounter, as well as the scaling characteristics and its real-time behaviour.
In this paper, we present our processing pipeline which enables parallel observations. The pipeline receives up to 198~Gb/s, and performs signal-processing techniques, weighted addition, and two all-to-all exchanges, and outputs up to 80~Gb/s. We present the trade-offs in our design, the CPU and I/O performance bottlenecks that we encounter, as well as the scaling characteristics and its real-time behaviour.
