Real-Time Dedispersion for Fast Radio Transient Surveys, using Auto Tuning on Many-Core Accelerators

Dedispersion, the removal of deleterious smearing of impulsive signals by the interstellar matter, is one of the most intensive processing steps in any radio survey for pulsars and fast transients. We here present a study of the parallelization of this algorithm on many-core accelerators, including GPUs from AMD and NVIDIA, and the Intel Xeon Phi. We find that dedispersion is inherently memory-bound. Even in a perfect scenario, hardware limitations keep the arithmetic intensity low, thus limiting performance. We next exploit auto-tuning to adapt dedispersion to different accelerators, observations, and even telescopes. We demonstrate that the optimal settings differ between observational setups, and that auto-tuning significantly improves performance. This impacts time-domain surveys from Apertif to SKA.Comment: 8 pages, accepted for publication in Astronomy and Computin

Chromatic periodic activity down to 120 MHz in a Fast Radio Burst

Fast radio bursts (FRBs) are extragalactic astrophysical transients whose brightness requires emitters that are highly energetic, yet compact enough to produce the short, millisecond-duration bursts. FRBs have thus far been detected between 300 MHz and 8 GHz, but lower-frequency emission has remained elusive. A subset of FRBs is known to repeat, and one of those sources, FRB 20180916B, does so with a 16.3 day activity period. Using simultaneous Apertif and LOFAR data, we show that FRB 20180916B emits down to 120 MHz, and that its activity window is both narrower and earlier at higher frequencies. Binary wind interaction models predict a narrower periodic activity window at lower frequencies, which is the opposite of our observations. Our detections establish that low-frequency FRB emission can escape the local medium. For bursts of the same fluence, FRB 20180916B is more active below 200 MHz than at 1.4 GHz. Combining our results with previous upper-limits on the all-sky FRB rate at 150 MHz, we find that there are 3-450 FRBs/sky/day above 50 Jy ms at 90% confidence. We are able to rule out the scenario in which companion winds cause FRB periodicity. We also demonstrate that some FRBs live in clean environments that do not absorb or scatter low-frequency radiation.Comment: 50 pages, 14 figures, 3 tables, submitte

Microbial associates and social behavior in ants

Current research in life sciences provides advances on how animal-associated microbes affect behavior and its underlying neurophysiology. However, studies in this field are often limited to individuals outside of their social context and neglect social dynamics. Contrarily, animals and humans develop and live in complex societies where they constantly adjust physiology and behavior to social interactions. To improve our understanding of how microbes and hosts interact and produce phenotypes at social and group levels, we need to broaden our experimental approaches to a group-level dimension. Here, we point out that eusocial insects, and ants in particular, are ideal models for this purpose. We first examine the most common types of microorganismal associations that ants engage in, and then briefly summarize what is known about the role of symbiotic microbes in ant social behavior. Finally, we propose future directions in the field, in the light of recent technical advances in behavior measuring techniques.Accepted versio

AA-ALERT/AMBER: Minor update

Small documentation change.</p

Finding Pulsars in Real-Time

Finding new pulsars has always been a challenging problem, but this challenge is nowadays exacerbated by the increasing data rates of modern radio telescopes. Because of these increased data rates, traditional approaches to searching, based on storing data for off-line processing, are becoming unfeasible. Therefore, we propose a new pulsar searching pipeline that, by exploiting high-performance computing techniques, is able to process observational data in real-time. To achieve the real-time goal we parallelized all the steps of the pipeline to run on many-core accelerators, and used auto-tuning to adapt and optimize the pipeline for different platforms, telescopes, and searching parameters. In this paper, we test our pipeline on three different platforms: two Graphics Processing Units from AMD and NVIDIA, and an Intel Xeon Phi. Furthermore, we test it on three different scenarios, based on the operational parameters of three state-of-the-art telescopes. Results show that our pipeline can adapt to all tested platforms and scenarios, and achieves real-time performance and linear scalability. Because power consumption is a main concern for radio telescopes, and will be the main bottleneck for the construction of the Square Kilometer Array, we also measure the power consumed by our pipeline. By comparing the results obtained on many-core accelerators with the results obtained using a traditional multi-core CPU, we conclude that the accelerators can provide up to a factor 8 improvement in execution time, and up to a factor 6 reduction in power consumption

Integrating real-time data analysis into automatic tracking of social insects

Automatic video tracking has become a standard tool for investigating the social behaviour of insects. The recent integration of computer vision in tracking technologies will probably lead to fully automated behavioural pattern classification within the next few years. However, many current systems rely on offline data analysis and use computationally expensive techniques to track pre-recorded videos. To address this gap, we developed BACH (Behaviour Analysis maCHine), a software that performs video tracking of insect groups in real time. BACH uses object recognition via convolutional neural networks and identifies individually tagged insects via an existing matrix code recognition algorithm. We compared the tracking performances of BACH and a human observer (HO) across a series of short videos of ants moving in a two-dimensional arena. We found that BACH detected ant shapes only slightly worse than the HO. However, its matrix code-mediated identification of individual ants only attained human-comparable levels when ants moved relatively slowly, and fell when ants walked relatively fast. This happened because BACH had a relatively low efficiency in detecting matrix codes in blurry images of ants walking at high speeds. BACH needs to undergo hardware and software adjustments to overcome its present limits. Nevertheless, our study emphasizes the possibility of, and the need for, further integrating real-time data analysis into the study of animal behaviour. This will accelerate data generation, visualization and sharing, opening possibilities for conducting fully remote collaborative experiments.Nanyang Technological UniversityPublished versionThis work was supported by a Presidential Postdoctoral Fellowship (grant no. M408080000) from NanyangTechnological University (NTU) to S.T