TENSILE: A Tensor granularity dynamic GPU memory scheduling method towards multiple dynamic workloads system

Recently, deep learning has been an area of intense research. However, as a kind of computing-intensive task, deep learning highly relies on the scale of GPU memory, which is usually prohibitive and scarce. Although there are some extensive works have been proposed for dynamic GPU memory management, they are hard to be applied to systems with multiple dynamic workloads, such as in-database machine learning systems. In this paper, we demonstrated TENSILE, a method of managing GPU memory in tensor granularity to reduce the GPU memory peak, considering the multiple dynamic workloads. TENSILE tackled the cold-starting and across-iteration scheduling problem existing in previous works. We implement TENSILE on a deep learning framework built by ourselves and evaluated its performance. The experiment results show that TENSILE can save more GPU memory with less extra time overhead than prior works in both single and multiple dynamic workloads scenarios

An outbreak of aseptic meningitis caused by a distinct lineage of coxsackievirus B5 in China

SummaryIn 2009, an outbreak of aseptic meningitis caused by coxsackievirus B5 (CVB5) occurred in China. Epidemiological investigations of this outbreak revealed that the proportion of severe cases (14/43, 33%) was higher than in other outbreaks associated with CVB5 in China. Phylogenetic analysis of the entire VP1 sequences demonstrated that the CVB5 isolates from the severe cases form a distinct lineage belonging to genogroup E with the Shandong isolates of 2009. A substitution of serine (S) to asparagine (N) at amino acid 95 in the VP1 region may be a major virulence determinant for the virus. Our findings suggest that this new lineage of CVB5 is circulating in China. Further genetic studies are needed in order to gain a better insight into the genetic variability of CVB5 isolates and the relationship with pathogenicity

Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives

Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites relevant to a specific phenotypic characteristic can be identified. However, the reliability of the analytical data is a prerequisite for correct biological interpretation in metabolomics analysis. In this review the challenges in quantitative metabolomics analysis with regards to analytical as well as data preprocessing steps are discussed. Recommendations are given on how to optimize and validate comprehensive silylation-based methods from sample extraction and derivatization up to data preprocessing and how to perform quality control during metabolomics studies. The current state of method validation and data preprocessing methods used in published literature are discussed and a perspective on the future research necessary to obtain accurate quantitative data from comprehensive GC-MS data is provided

A global urban land expansion product at 1-km resolution for 2015 to 2100 based on the SSP scenarios

Despite its small land coverage, urban land and its expansion can have profound impacts on global environments. Therefore, a proper understanding of how future urban land change will affect other land covers is important to alleviate the social and environmental problems that challenge the sustainable developments of human societies. Recently, The Shared Socioeconomic Pathways (SSPs) were adopted by the Coupled Model Intercomparison Project Phase 6 (CMIP6), enabling researchers to conduct unified, comparable multi-scenario simulations and integrate such simulation products into climate change research. The SSPs focus on the key socio-economic factors including demographic dynamics, economic development, technological change, social, cultural, and institutional changes and policies. Here, we present the scenario projections of global urban land expansion under the framework of the shared socioeconomic pathways (SSPs) every 10 years from 2015 to 2100. Our projections feature a fine spatial resolution of 1 km that preserves spatial details and avoids potential distortions in urban land patterns. The objective is to enable the assessment of different scenarios of future urban expansion and their related impacts on a global scale under the latest recognized SSP scenarios