The On-Site Analysis of the Cherenkov Telescope Array

Abstract

2 PoS(ICRC2015)763The Cherenkov Telescope Array (CTA) observatory will be one of the largest ground-based veryhigh-energy gamma-ray observatories. The On-Site Analysis will be the first CTA scientific analysis of data acquired from the array of telescopes, in both northern and southern sites. The On-Site Analysis will have two pipelines: the Level-A pipeline (also known as Real-Time Analysis, RTA) and the level-B one. The RTA performs data quality monitoring and must be able to issue automated alerts on variable and transient astrophysical sources within 30 seconds from the last acquired Cherenkov event that contributes to the alert, with a sensitivity not worse than the one achieved by the final pipeline by more than a factor of 3. The Level-B Analysis has a better sensitivity (not be worse than the final one by a factor of 2) and the results should be available within 10 hours from the acquisition of the data: for this reason this analysis could be performed at the end of an observation or next morning. The latency (in particular for the RTA) and the sensitivity requirements are challenging because of the large data rate, a few GByte/s. The remote connection to the CTA candidate site with a rather limited network bandwidth makes the issue of the exported data size extremely critical and prevents any kind of processing in real-time of the data outside the site of the telescopes. For these reasons the analysis will be performed on-site with infrastructures co-located with the telescopes, with limited electrical power availability and with a reduced possibility of human intervention. This means, for example, that the on-site hardware infrastructure should have low-power consumption. A substantial effort towards the optimization of high-throughput computing service is envisioned to provide hardware and software solutions with high-throughput, low-power consumption at a low-cost. This contribution provides a summary of the design of the on-site analysis and reports some prototyping activities.

Cherenkov Telescope Array Data Management

“…Main prototyping activities were around the evaluation of software frameworks based on C/C++ languages, Python, Hadoop using modern MapReduce computing method. Further comparative studies concerned: adapting FITS data format to Hadoop files management methods, combining Python and C++ for inter-process communication in the context of the real-time data streaming [2] with FPGA and GPU hardware accelerators.…”

Real-Time Analysis sensitivity evaluation of the Cherenkov Telescope Array

“…Given the flaring and transient nature of many VHE sources, the CTA observatory will couple the unprecedented sensitivity to another performance driver: the fast reaction to VHE events, achieved by means of the Real-Time Analysis (RTA) science alert system [9]. The RTA pipeline, one of the products of the CTA On-Site Analysis (OSA, [10]), will automatically detect sub-minute emission and generate science alerts with a latency of 30 seconds with respect to the triggering event collection, allowing both rapid telescope re-pointings and communications (e.g. Virtual Observatory alerts) to external observatories, and making CTA a crucial instrument for the observation of the gamma-ray flaring sky.…”

Status and plans for the Array Control and Data Acquisition System of the Cherenkov Telescope Array

“…for the long-term scheduling), accept incoming alerts (e.g. directly from other observatories or in connection with target of opportunities), and manage the execution (but not the implementation) of a real time analysis software (see [4] for details).…”

“…The DAQ will comprise the camera readout, the buffering of the read-out data, the processing of array trigger decisions, the building of camera-dependent events and filtering of interesting events to reduce the overall data volume (about 20 PB/y). Further data volume reduction is planned to be achieved via the data analysis pipeline running on site [4]. A compact and flexible data format is planned to be used since the amount of data to be read out depends strongly on the camera type which in turn determines parameters like the camera trigger rate, the sampling rate and the decision as to whether waveform information is being included or not.…”

“…The computing nodes are used to deploy the ACTL software components as well as the data analysis procedures described in [4]. A total need of about 1500 cores (x86 architecture) for the CTA southern array (870 for northern one) is estimated from current software prototypes.The on-site storage system will be entirely assembled from basic storage units consisting of one storage node server equipped with internally connected disks.…”