No Arabic abstract
Astronomy is entering in a new era of Extreme Intensive Data Computation and we have identified three major issues the new generation of projects have to face: Resource optimization, Heterogeneous Software Ecosystem and Data Transfer. We propose in this article a middleware solution offering a very modular and maintainable system for data analysis. As computations must be designed and described by specialists in astronomy, we aim at defining a friendly specific programming language to enable coding of astrophysical problems abstracted from any computer science specific issues. This way we expect substantial benefits in computing capabilities in data analysis. As a first development using our solution, we propose a cross-matching service for the Taiwan Extragalactic Astronomical Data Center.
The increasing volumes of astronomical data require practical methods for data exploration, access and visualisation. The Hierarchical Progressive Survey (HiPS) is a HEALPix based scheme that enables a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. We highlight the decisions and approaches that have been taken to make this scheme a practical solution for managing large volumes of heterogeneous data. Early implementors of this system have formed a network of HiPS nodes, with some 250 diverse data sets currently available, with multiple mirror implementations for important data sets. This hierarchical approach can be adapted to expose Big Data in different ways. We describe how the ease of implementation, and local customisation of the Aladin Lite embeddable HiPS visualiser have been keys for promoting collaboration on HiPS.
GNU Data Language (GDL) is an open-source interpreted language aimed at numerical data analysis and visualisation. It is a free implementation of the Interactive Data Language (IDL) widely used in Astronomy. GDL has a full syntax compatibility with IDL, and includes a large set of library routines targeting advanced matrix manipulation, plotting, time-series and image analysis, mapping, and data input/output including numerous scientific data formats. We will present the current status of the project, the key accomplishments, and the weaknesses - areas where contributions are welcome !
Interferometric radio telescopes often rely on computationally expensive O(N^2) correlation calculations; fortunately these computations map well to massively parallel accelerators such as low-cost GPUs. This paper describes the OpenCL kernels developed for the GPU based X-engine of a new hybrid FX correlator. Channelized data from the F-engine is supplied to the GPUs as 4-bit, offset-encoded real and imaginary integers. Because of the low bit width of the data, two values may be packed into a 32-bit register, allowing multiplication and addition of more than one value with a single fused multiply-add instruction. With this data and calculation packing scheme, as many as 5.6 effective tera-operations per second (TOPS) can be executed on a 4.3 TOPS GPU. The kernel design allows correlations to scale to large numbers of input elements, limited only by maximum buffer sizes on the GPU. This code is currently working on-sky with the CHIME Pathfinder Correlator in BC, Canada.
Measuring scientific development is a difficult task. Different metrics have been put forward to evaluate scientific development; in this paper we explore a metric that uses the number of peer-reviewed, and when available non-peer-reviewed articles, research research articles as an indicator of development in the field of astronomy. We analyzed the available publication record, using the SAO/NASA Astrophysics Database System, by country affiliation in the time span between 1950 and 2011 for countries with a Gross National Income of less than 14,365 USD in 2010. This represents 149 countries. We propose that this metric identifies countries in `astronomy development with a culture of research publishing. We also propose that for a country to develop astronomy it should invest in outside expert visits, send their staff abroad to study and establish a culture of scientific publishing. Furthermore, we propose that this paper may be used as a baseline to measure the success of major international projects, such as the International Year of Astronomy 2009.
Nowadays astroparticle physics faces a rapid data volume increase. Meanwhile, there are still challenges of testing the theoretical models for clarifying the origin of cosmic rays by applying a multi-messenger approach, machine learning and investigation of the phenomena related to the rare statistics in detecting incoming particles. The problems are related to the accurate data mapping and data management as well as to the distributed storage and high-performance data processing. In particular, one could be interested in employing such solutions in study of air-showers induced by ultra-high energy cosmic and gamma rays, testing new hypotheses of hadronic interaction or cross-calibration of different experiments. KASCADE (Karlsruhe, Germany) and TAIGA (Tunka valley, Russia) are experiments in the field of astroparticle physics, aiming at the detection of cosmic-ray air-showers, induced by the primaries in the energy range of about hundreds TeVs to hundreds PeVs. They are located at the same latitude and have an overlap in operation runs. These factors determine the interest in performing a joint analysis of these data. In the German-Russian Astroparticle Data Life Cycle Initiative (GRADLCI), modern technologies of the distributed data management are being employed for establishing a reliable open access to the experimental cosmic-ray physics data collected by KASCADE and the Tunka-133 setup of TAIGA.