High resolution spectroscopy of the BCD galaxy Haro 15:I. Internal kinematics

Using echelle spectroscopy, obtained at Las Campanas Observatory, we present a detailed study of the internal kinematics of the nebular material in multiple knots of the blue compact dwarf galaxy Haro 15. A detailed analysis of the complex emission line profiles show the presence of an underlying broad component in almost all knots, and the brightest star-forming region shows unmistakable signs for the presence of two distinct narrow kinematical components. We also study the information that our analysis provides regarding the motion of the individual knots in the Haro 15 galaxy potential, confirming that they follow galactic rotation. Finally, we examine the relation between their velocity dispersion and luminosity, finding that almost all knots follow the relation for virialised systems. This holds for the strong narrow components identified in complex fits and for single profile fits, although the latter show a flatter slope. In agreement with previous findings, in this paper we show that the existence of multiple kinematical components among massive starbursts cannot be overlooked, as it has a noticeable effect on any subsequent analysis that relies on basic parameters.Comment: 12 pages, 21 figure

Improvements in Hardware Transactional Memory for GPU Architectures

In the multi-core CPU world, transactional memory (TM)has emerged as an alternative to lock-based programming for thread synchronization. Recent research proposes the use of TM in GPU architectures, where a high number of computing threads, organized in SIMT fashion, requires an effective synchronization method. In contrast to CPUs, GPUs offer two memory spaces: global memory and local memory. The local memory space serves as a shared scratch-pad for a subset of the computing threads, and it is used by programmers to speed-up their applications thanks to its low latency. Prior work from the authors proposed a lightweight hardware TM (HTM) support based in the local memory, modifying the SIMT execution model and adding a conflict detection mechanism. An efficient implementation of these features is key in order to provide an effective synchronization mechanism at the local memory level. After a quick description of the main features of our HTM design for GPU local memory, in this work we gather together a number of proposals designed with the aim of improving those mechanisms with high impact on performance. Firstly, the SIMT execution model is modified to increase the parallelism of the application when transactions must be serialized in order to make forward progress. Secondly, the conflict detection mechanism is optimized depending on application characteristics, such us the read/write sets, the probability of conflict between transactions and the existence of read-only transactions. As these features can be present in hardware simultaneously, it is a task of the compiler and runtime to determine which ones are more important for a given application. This work includes a discussion on the analysis to be done in order to choose the best configuration solution.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Soft Communities in Similarity Space

The S1 model has been central in the development of the field of network geometry. It places nodes in a similarity space and connects them with a likelihood depending on an effective distance which combines similarity and popularity dimensions, with popularity directly related to the degrees of the nodes. The S1 model has been mainly studied in its homogeneous regime, in which angular coordinates are independently and uniformly scattered on the circle. We now investigate if the model can generate networks with targeted topological features and soft communities, that is, inhomogeneous angular distributions. To that end, hidden degrees must depend on angular coordinates, and we propose a method to estimate them. We conclude that the model can be topologically invariant with respect to the soft-community structure. Our results expand the scope of the model beyond the independent hidden variables limit and can have an important impact in the embedding of real-world networks