PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

High-performance computing has recently seen a surge of interest in heterogeneous systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices offer tremendous potential for performance and efficiency in important large-scale applications of computational science. However, exploiting this potential can be challenging, as one must adapt to the specialized and rapidly evolving computing environment currently exhibited by GPUs. One way of addressing this challenge is to embrace better techniques and develop tools tailored to their needs. This article presents one simple technique, GPU run-time code generation (RTCG), along with PyCUDA and PyOpenCL, two open-source toolkits that support this technique. In introducing PyCUDA and PyOpenCL, this article proposes the combination of a dynamic, high-level scripting language with the massive performance of a GPU as a compelling two-tiered computing platform, potentially offering significant performance and productivity advantages over conventional single-tier, static systems. The concept of RTCG is simple and easily implemented using existing, robust infrastructure. Nonetheless it is powerful enough to support (and encourage) the creation of custom application-specific tools by its users. The premise of the paper is illustrated by a wide range of examples where the technique has been applied with considerable success.Comment: Submitted to Parallel Computing, Elsevie

Bivariate galaxy luminosity functions in the Sloan Digital Sky Survey

Bivariate luminosity functions (LFs) are computed for galaxies in the New York Value-Added Galaxy Catalogue, based on the Sloan Digital Sky Survey Data Release 4. The galaxy properties investigated are the morphological type, inverse concentration index, Sérsic index, absolute effective surface brightness (SB), reference frame colours, absolute radius, eClass spectral type, stellar mass and galaxy environment. The morphological sample is flux limited to galaxies with r < 15.9 and consists of 37 047 classifications to an rms accuracy of ± half a class in the sequence E, S0, Sa, Sb, Sc, Sd, Im. These were assigned by an artificial neural network, based on a training set of 645 eyeball classifications. The other samples use r < 17.77 with a median redshift of z∼ 0.08, and a limiting redshift of z < 0.15 to minimize the effects of evolution. Other cuts, for example in axis ratio, are made to minimize biases. A wealth of detail is seen, with clear variations between the LFs according to absolute magnitude and the second parameter. They are consistent with an early-type, bright, concentrated, red population and a late-type, faint, less concentrated, blue, star-forming population. This bimodality suggests two major underlying physical processes, which in agreement with previous authors we hypothesize to be merger and accretion, associated with the properties of bulges and discs, respectively. The bivariate luminosity–SB distribution is fit with the Chołoniewski function (a Schechter function in absolute magnitude and Gaussian in SB). The fit is found to be poor, as might be expected if there are two underlying processes

Investigation related to multispectral imaging systems

A summary of technical progress made during a five year research program directed toward the development of operational information systems based on multispectral sensing and the use of these systems in earth-resource survey applications is presented. Efforts were undertaken during this program to: (1) improve the basic understanding of the many facets of multispectral remote sensing, (2) develop methods for improving the accuracy of information generated by remote sensing systems, (3) improve the efficiency of data processing and information extraction techniques to enhance the cost-effectiveness of remote sensing systems, (4) investigate additional problems having potential remote sensing solutions, and (5) apply the existing and developing technology for specific users and document and transfer that technology to the remote sensing community

Advanced Moisture and Temperature Sounder (AMTS) study

Retrieval of tropospheric humidity profiles from satellite-based upwelling radiances are shown to be improved by using physical methods for obtaining first-guess profiles as well as for inverting the radiative transfer equation by relaxation. The first guess is based on an empirically verified hypothesis, from theoretical considerations, that the brightness temperature corresponding to the radiance should be approximately equal to the actual temperatue at a channel-invariant optical depth provided that the surface and stratospheric contributions to the radiance are small. Even greater improvement of retrieved humidity profiles can be accomplished by increasing the number of channels used and by selecting their spectral location and bandpass to obtain sharper independent weighting functions. For example, the AMTS system, with high resolution water channels at 1650, 1700, 1839, 1850 and 1930 cm, is shown to be capable of reducing the retrieved water vapor errors in 200 mb thick layers by a factor of two or three relative to the HIRS-2 system errors. Expected AMTS errors in tropical layer water content are particularly low, less than 20% at all levels, and of the order of 10% or less in the middle troposphere