Grid Search in Stellar Parameters: a software for spectrum analysis of single stars and binary systems

The currently operating space missions, as well as those that will be launched in the near future, (will) deliver high-quality data for millions of stellar objects. Since the majority of stellar astrophysical applications still (at least partly) rely on spectroscopic data, an efficient tool for the analysis of medium- to high-resolution spectroscopy is needed. We aim at developing an efficient software package for the analysis of medium- to high-resolution spectroscopy of single stars and those in binary systems. The major requirements are that the code has a high performance, represents the state-of-the-art analysis tool, and provides accurate determinations of atmospheric parameters and chemical compositions for different types of stars. We use the method of atmosphere models and spectrum synthesis, which is one of the most commonly used approaches for the analysis of stellar spectra. Our Grid Search in Stellar Parameters (GSSP) code makes use of the OpenMPI implementation, which makes it possible to run in parallel mode. The method is first tested on the simulated data and is then applied to the spectra of real stellar objects. The majority of test runs on the simulated data were successful in the sense that we could recover the initially assumed sets of atmospheric parameters. We experimentally find the limits in signal-to-noise ratios of the input spectra, below which the final set of parameters gets significantly affected by the noise. Application of the GSSP package to the spectra of three Kepler stars, KIC11285625, KIC6352430, and KIC4931738, was also largely successful. We found an overall agreement of the final sets of the fundamental parameters with the original studies. For KIC6352430, we found that dependence of the light dilution factor on wavelength cannot be ignored, as it has significant impact on the determination of the atmospheric parameters of this binary system.Comment: 19 pages, 6 figures, 4 tables, 2 appendices one of which includes detailed description of input and output files. Accepted for publication in Astronomy & Astrophysi

Optimizing Splicing Junction Detection in Next Generation Sequencing Data on a Virtual-GRID Infrastructure

The new protocol for sequencing the messenger RNA in a cell, named RNA-seq produce millions of short sequence fragments. Next Generation Sequencing technology allows more accurate analysis but increase needs in term of computational resources. This paper describes the optimization of a RNA-seq analysis pipeline devoted to splicing variants detection, aimed at reducing computation time and providing a multi-user/multisample environment. This work brings two main contributions. First, we optimized a well-known algorithm called TopHat by parallelizing some sequential mapping steps. Second, we designed and implemented a hybrid virtual GRID infrastructure allowing to efficiently execute multiple instances of TopHat running on different samples or on behalf of different users, thus optimizing the overall execution time and enabling a flexible multi-user environmen

Preparing HPC Applications for the Exascale Era: A Decoupling Strategy

Production-quality parallel applications are often a mixture of diverse operations, such as computation- and communication-intensive, regular and irregular, tightly coupled and loosely linked operations. In conventional construction of parallel applications, each process performs all the operations, which might result inefficient and seriously limit scalability, especially at large scale. We propose a decoupling strategy to improve the scalability of applications running on large-scale systems. Our strategy separates application operations onto groups of processes and enables a dataflow processing paradigm among the groups. This mechanism is effective in reducing the impact of load imbalance and increases the parallel efficiency by pipelining multiple operations. We provide a proof-of-concept implementation using MPI, the de-facto programming system on current supercomputers. We demonstrate the effectiveness of this strategy by decoupling the reduce, particle communication, halo exchange and I/O operations in a set of scientific and data-analytics applications. A performance evaluation on 8,192 processes of a Cray XC40 supercomputer shows that the proposed approach can achieve up to 4x performance improvement.Comment: The 46th International Conference on Parallel Processing (ICPP-2017

A posteriori inclusion of PDFs in NLO QCD final-state calculations

Any NLO calculation of a QCD final-state observable involves Monte Carlo integration over a large number of events. For DIS and hadron colliders this must usually be repeated for each new PDF set, making it impractical to consider many `error' PDF sets, or carry out PDF fits. Here we discuss ``a posteriori'' inclusion of PDFs, whereby the Monte Carlo run calculates a grid (in x and Q) of cross section weights that can subsequently be combined with an arbitrary PDF. The procedure is numerically equivalent to using an interpolated form of the PDF. The main novelty relative to prior work is the use of higher-order interpolation, which substantially improves the tradeoff between accuracy and memory use. An accuracy of about 0.01% has been reached for the single inclusive cross-section in the central rapidity region |y|<0.5 for jet transverse momenta from 100 to 5000 GeV. This method should facilitate the consistent inclusion of final-state data from HERA, Tevatron and LHC in PDF fits, thus helping to increase the sensitivity of LHC to deviations from standard Model predictions.Comment: contribution to the CERN DESY workshop on "HERA and LHC