What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big Data (up to terabytes or petabytes)? Modern parallelization strategies employ fine-grained operations and scheduling beyond the classic bulk-synchronous processing paradigm popularized by MapReduce, or even specialized graph-based execution that relies on graph representations of ML programs. The variety of approaches tends to pull systems and algorithms design in different directions, and it remains difficult to find a universal platform applicable to a wide range of ML programs at scale. We propose a general-purpose framework that systematically addresses data-and model-parallel challenges in large-scale ML, by observing that many ML programs are fundamentally optimization-centric and admit error-tolerant, iterative-convergent algorithmic solutions. This presents unique opportunities for an integrative system design, such as bounded-error network synchronization and dynamic scheduling based on ML program structure. We demonstrate the efficacy of these system designs versus well-known implementations of modern ML algorithms, allowing ML programs to run in much less time and at considerably larger model sizes, even on modestly-sized compute clusters.
Regional precipitation recycling is the measure of the contribution of local evaporation E to local precipitation. This study provides a set of two methods developed in the Weather Research and Forecasting WRF model system for investigating regional precipitation recycling mechanisms: (1) tracking of tagged atmospheric water species originating from evaporation in a source region, ie E-tagging, and (2) three-dimensional budgets of total and tagged atmospheric water species. These methods are used to quantify the effect of return flow and nonwell vertical mixing neglected in the computation of the bulk precipitation recycling ratio. The developed algorithms are applied to a WRF simulation of the West African Monsoon 2003. The simulated region is characterized by vertical wind shear condition, i.e., southwesterlies in the low levels and easterlies in the mid-levels, which favors return flow and nonwell vertical mixing. Regional precipitation recycling is investigated in 100 3 100 and 1000 3 1000 km 2 areas. A prerequisite condition for evaporated water to contribute to the precipitation process in both areas is that it is lifted to the mid-levels where hydrometeors are produced. In the 100 3 100 (1000 3 1000) km 2 area the bulk precipitation recycling ratio is 0.9 (7.3) %. Our budget analysis reveals that return flow and nonwell vertically mixed outflow increase this value by about 10.2 (2.9) and 10.2 (1.6) %, respectively, thus strengthening the well-known scale-dependency of regional precipitation recycling.
Aims: The ecological characteristics of the deep‐sea amoA‐encoding archaea (AEA) are largely unsolved. Our aim was to study the diversity, structure and distribution of the AEA community in the sediments of the tropical West Pacific Continental Margin, to develop a general view of the AEA biogeography in the deep‐sea extreme environment. Methods and Results: Archaeal amoA clone libraries were constructed. Diverse and novel amoA sequences were identified, with the Bohol Sea, Bashi Strait and Sibuyan Sea harbouring the highest and the Bicol Shelf the lowest AEA diversity. Phylogenetic and statistical analyses illustrate a heterogeneous distribution of the AEA community, probably caused by the differential distribution of the terrestrial or estuarine AEA in the various sampling sites. Conclusions: The deep‐sea sedimentary environments potentially harbour diverse and novel AEA in the tropical West Pacific Continental Margin. The stations in the Philippine inland seas (including station 3043) may represent AEA assemblages with various terrestrial influences and the stations connected directly to the open Philippine Sea may represent marine environment‐dominant AEA assemblages. Significance and Impact of Study: Our study indicates the potential importance of geological and climatic events in the transport of terrestrial micro‐organisms to the deep‐sea sedimentary environments, almost totally neglected previously.
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