A survey of self-awareness and its application in computing systems

Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems

Using the Cloud for Parameter Estimation Problems: Comparing Spark vs MPI with a Case-Study

Date of Conference: 14-17 May 2017. Conference Location: Madrid[Abstract] Systems biology is an emerging approach focused in generating new knowledge about complex biological systems by combining experimental data with mathematical modeling and advanced computational techniques. Many problems in this field are extremely challenging and require substantial supercomputing resources to be solved. This is the case of parameter estimation in large-scale nonlinear dynamic systems biology models. Recently, Cloud Computing has emerged as a new paradigm for on-demand delivery of computing resources. However, scientific computing community has been quite hesitant in using the Cloud, simply because traditional programming models do not fit well with the new paradigm, and the earliest cloud programming models do not allow most scientific computations being efficiently run in the Cloud. In this paper we explore and compare two distributed computing models: the MPI (message-passing interface) model, that is high-performance oriented, and the Spark model, which is throughput oriented but outperforms other cloud programming solutions adding improved support for iterative algorithms through in-memory computing. The performance of a very well known metaheuristic, the Differential Evolution algorithm, has been thoroughly assessed using a challenging parameter estimation problem from the domain of computational systems biology. The experiments have been carried out both in a local cluster and in the Microsoft Azure public cloud, allowing performance and cost evaluation for both infrastructures.Gobierno de España; DPI2014-55276-C5-2-RFondos Feder; TIN2016-75845-PXunta de Galicia; R2016/045Xunta de Galicia; GRC2013/05

Accelerating Exact Stochastic Simulation of Biochemical Systems

The ability to accurately and efficiently simulate computer models of biochemical systems is of growing importance to the molecular biology and pharmaceutical research communities. Exact stochastic simulation is a popular approach for simulating such systems because it properly represents genetic noise and it accurately represents systems with small populations of chemical species. Unfortunately, the computational demands of exact stochastic simulation often limit its applicability. To enable next-generation whole-cell and multi-cell stochastic modeling, advanced tools and techniques must be developed to increase simulation efficiency. This work assesses the applicability of a variety of hardware and software acceleration approaches for exact stochastic simulation including serial algorithm improvements, parallel computing, reconfigurable computing, and cluster computing. Through this analysis, improved simulation techniques for biological systems are explored and evaluated

Capturing Multicellular System Designs Using Synthetic Biology Open Language (SBOL)

8 Pág.Synthetic biology aims to develop novel biological systems and increase their reproducibility using engineering principles such as standardization and modularization. It is important that these systems can be represented and shared in a standard way to ensure they can be easily understood, reproduced, and utilized by other researchers. The Synthetic Biology Open Language (SBOL) is a data standard for sharing biological designs and information about their implementation and characterization. Previously, this standard has only been used to represent designs in systems where the same design is implemented in every cell; however, there is also much interest in multicellular systems, in which designs involve a mixture of different types of cells with differing genotype and phenotype. Here, we show how the SBOL standard can be used to represent multicellular systems, and, hence, how researchers can better share designs with the community and reliably document intended system functionality.This work was supported in part by NSF Expeditions in Computing Program Award No. 1522074 as part of the Living Computing Project and by the Defense Advanced Research Projects Agency under Contract No. W911NF-17-2-0098. The views, opinions, and/or findings expressed are of the author(s) and should not be interpreted as representing official views or policies of the Department of Defense or the U.S. Government. A.G.-M. was supported by the SynBio3D project of the UK Engineering and Physical Sciences Research Council (No.EP/R019002/1) and the European CSA on biological standardization BIOROBOOST (EU Grant No. 820699)Peer reviewe

Genomic cloud computing:Legal and ethical points to consider

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.</p

Constraints on Patterns of Abundance and Aggregation in Biological Systems

Understanding the mechanisms that structure biological systems is a primary goal of biology. My research shows that the biological structure is constrained in important ways by general variables such as the number of base pairs in a genome and the number of individuals and species in a community. I used a combination of macroecology, bioinformatics, statistics, mathematics, and advanced computing to pursue my research and published several peer-reviewed scientific manuscripts and open-source software as a result.I was funded through a combination of fellowships and scholarships awarded by the Utah State University School of Graduate Studies, College of Science, and Department of Biology, as well as teaching assistantships awarded through the Department of Biology at Utah State University, and research assistantships funded through a CAREER grant from the U.S. National Science Foundation (DEB-0953694) awarded to my advisor, Dr. Ethan White. With the help of my advisor, I also obtained a computing grant from Amazon Web Services in the amount of $7,500. Altogether, funding for my research and education totaled approximately$123,500. Using over 9000 communities of plants, animals, fungi, and microorganisms, I demonstrated that the forms of empirical species abundance distributions (SADs) are constrained by total abundance and species richness. Using over 300 microbial genomes, I demonstrate that nucleotide aggregation is constrained by genome length and differs between regions of coding and noncoding DNA. General state variables of genomes and ecological communities (i.e. genome length, total abundance and species richness) constrain simple structural properties of each system

Український академічний Грід: досвід створення й перші результати експлуатації

Описано особливості побудови та перші результати застосування Грід-інфраструктури Національної академії наук України. Наведено історичні відомості про побудову Грід-систем в Україні. Сформульовано основні вимоги до обчислювальних ресурсів, каналів передачі даних та проміжного програмного забезпечення. Обґрунтовано вибір концепції Beowulf-кластерів та проміжного програмного забезпечення Advanced resource connector (ARC). Наведено характеристики кластерних установок Грід-інфраструктури та результати практичного застосування системи для розв’язання задач фізики, біології, інформаційних технологій. Табл.: 2. Іл.: 4. Бібліогр.: 10 назв.Описаны особенности построения и первые результаты использования Грид-инфраструктуры Национальной академии наук Украины. Приведены исторические сведения о создании Грид-систем в Украине. Сформулированы основные требования к вычислительным ресурсам, каналам передачи информации и промежуточному программному обеспечению. Обосновано выбор концепции кластеров типа Beowulf и промежуточного программного обеспечения Advanced resource connector (ARC). Приведены характеристики кластерных установок Грид-инфраструктуры и результаты ее практического использования для решения задач из областей физики, биологии, информационных технологий. Табл.: 2. Іл.: 4. Библиогр.: 10 назв.Paper describes design features of Grid-infrastructure of The National Academy of Sciences of Ukraine and the first results of its application. History of creation of Grid-systems in Ukraine is depicted. The main requirements for computing resources, communication channels and middleware are listed. Beowulf clusters concept and Advanced resource connector (ARC) middleware were chosen and approved. Technical characteristics Grid-infrastructure clusters and results of its practical application for physics, biology and information technology problems are listed. Tabl.: 2. Figs.: 4. Refs.: 10 titles

The Case for Improving U.S. Computer Science Education

Despite the growing use of computers and software in every facet of our economy, not until recently has computer science education begun to gain traction in American school systems. The current focus on improving science, technology, engineering, and mathematics (STEM) education in the U.S. school system has disregarded differences within STEM fields. Indeed, the most important STEM field for a modern economy is not only one that is not represented by its own initial in "STEM" but also the field with the fewest number of high school students taking its classes and by far has the most room for improvement—computer science