On-the-fly memory compression for multibody algorithms.

Memory and bandwidth demands challenge developers of particle-based codes that have to scale on new architectures, as the growth of concurrency outperforms improvements in memory access facilities, as the memory per core tends to stagnate, and as communication networks cannot increase bandwidth arbitrary. We propose to analyse each particle of such a code to find out whether a hierarchical data representation storing data with reduced precision caps the memory demands without exceeding given error bounds. For admissible candidates, we perform this compression and thus reduce the pressure on the memory subsystem, lower the total memory footprint and reduce the data to be exchanged via MPI. Notably, our analysis and transformation changes the data compression dynamically, i.e. the choice of data format follows the solution characteristics, and it does not require us to alter the core simulation code

On-the-fly memory compression for multibody algorithms

Memory and bandwidth demands challenge developers of particle-based codes that have to scale on new architectures, as the growth of concurrency outperforms improvements in memory access facilities, as the memory per core tends to stagnate, and as communication networks cannot increase bandwidth arbitrary. We propose to analyse each particle of such a code to find out whether a hierarchical data representation storing data with reduced precision caps the memory demands without exceeding given error bounds. For admissible candidates, we perform this compression and thus reduce the pressure on the memory subsystem, lower the total memory footprint and reduce the data to be exchanged via MPI. Notably, our analysis and transformation changes the data compression dynamically, i.e. the choice of data format follows the solution characteristics, and it does not require us to alter the core simulation code

UV and EUV Instruments

We describe telescopes and instruments that were developed and used for astronomical research in the ultraviolet (UV) and extreme ultraviolet (EUV) regions of the electromagnetic spectrum. The wavelength ranges covered by these bands are not uniquely defined. We use the following convention here: The EUV and UV span the regions ~100-912 and 912-3000 Angstroem respectively. The limitation between both ranges is a natural choice, because the hydrogen Lyman absorption edge is located at 912 Angstroem. At smaller wavelengths, astronomical sources are strongly absorbed by the interstellar medium. It also marks a technical limit, because telescopes and instruments are of different design. In the EUV range, the technology is strongly related to that utilized in X-ray astronomy, while in the UV range the instruments in many cases have their roots in optical astronomy. We will, therefore, describe the UV and EUV instruments in appropriate conciseness and refer to the respective chapters of this volume for more technical details.Comment: To appear in: Landolt-Boernstein, New Series VI/4A, Astronomy, Astrophysics, and Cosmology; Instruments and Methods, ed. J.E. Truemper, Springer-Verlag, Berlin, 201

Active Resource Management for Multi-Core Runtime Systems Serving Malleable Applications

Malleable applications are programs that may run with varying numbers of threads and thus on varying numbers of cores because the exact number of threads/cores used is irrelevant for the program logic and typically determined at program startup. We argue that any fixed choice of kernel threads is suboptimal for both performance and energy consumption. Firstly, an application may temporarily expose less concurrency than the underlying hardware offers, leading to waste of energy. Secondly, the number of hardware cores effectively available to an application may dynamically change in multi-application and/or multi-user environments. This leads to an over-subscription of the available hardware by individual applications, costly time scheduling by the operating system and, as a consequence, to both waste of energy and loss of performance. We propose an active resource management service that continuously mediates betwen dynamically changing intra-application requirements as well as on dynamically changing system load characteristics in a near-optimal way