39 research outputs found

    Stochastic Calculus of Wrapped Compartments

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    The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of Looping Sequences (CLS). While keeping the same expressiveness, CWC strongly simplifies the development of automatic tools for the analysis of biological systems. The main simplification consists in the removal of the sequencing operator, thus lightening the formal treatment of the patterns to be matched in a term (whose complexity in CLS is strongly affected by the variables matching in the sequences). We define a stochastic semantics for this new calculus. As an application we model the interaction between macrophages and apoptotic neutrophils and a mechanism of gene regulation in E.Coli

    A parallel edge preserving algorithm for salt and pepper image denoising

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    In this paper a two-phase filter for removing 'salt and pepper' noise is proposed. In the first phase, an adaptive median filter is used to identify the set of the noisy pixels; in the second phase, these pixels are restored according to a regularization method, which contains a data-fidelity term reflecting the impulse noise characteristics. The algorithm, which exhibits good performance both in denoising and in restoration, can be easily and effectively parallelized to exploit the full power of multi-core CPUs and GPGPUs; the proposed implementation based on the FastFlow library achieves both close-to-ideal speedup and very good wall-clock execution figures

    On dynamic memory allocation in sliding-window parallel patterns for streaming analytics

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    This work studies the issues related to dynamic memory management in Data Stream Processing, an emerging paradigm enabling the real-time processing of live data streams. In this paper, we consider two streaming parallel patterns and we discuss different implementation variants related to how dynamic memory is managed. The results show that the standard mechanisms provided by modern C++ are not entirely adequate for maximizing the performance. Instead, the combined use of an efficient general purpose memory allocator, a custom allocator optimized for the pattern considered and a custom variant of the C++ shared pointer mechanism, provides a performance improvement up to 16% on the best case

    Parallel Stochastic Simulators in System Biology: The Evolution of the Species

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    The stochastic simulation of biological systems is an increasingly popular technique in Bioinformatics. It is often an enlightening technique, especially for multi-stable systems which dynamics can be hardly captured with ordinary differential equations. To be effective, stochastic simulations should be supported by powerful statistical analysis tools. The simulation-analysis workflow may however result in being computationally expensive, thus compromising the interactivity required in model tuning. In this work we advocate the high-level design of simulators for stochastic systems as a vehicle for building efficient and portable parallel simulators. In particular, the Calculus of Wrapped Components (CWC) simulator, which is designed according to the FastFlow's pattern-based approach, is presented and discussed in this work. FastFlow has been extended to support also clusters of multi-cores with minimal coding effort, assessing the portability of the approach

    Modelling Ammonium Transporters in Arbuscular Mycorrhiza Symbiosis

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    The Stochastic Calculus ofWrapped Compartments (SCWC) is a recently proposed variant of the Stochastic Calculus of Looping Sequences (SCLS), a language for the representation and simulation of biological systems. In this work we apply SCWC to model a newly discovered ammonium transporter. This transporter is believed to play a fundamental role for plant mineral acquisition, which takes place in the arbuscular mycorrhiza, the most wide-spread plant-fungus symbiosis on earth. Investigating this kind of symbiosis is considered one of the most promising ways to develop methods to nurture plants in more natural manners, avoiding the complex chemical productions used nowadays to produce artificial fertilizers. In our experiments the passage of NH3 / NH+4 from the fungus to the plant has been dissected in known and hypothetical mechanisms; with the model so far we have been able to simulate the behavior of the system under different conditions. Our simulations confirmed some of the latest experimental results about the LjAMT2;2 transporter. Moreover, by comparing the behaviour of LjAMT2;2 with the behaviour of another ammonium transporter which exists in plants, viz. LjAMT1;1, our simulations support an hypothesis about why LjAMT2;2 is so selectively expressed in arbusculated cells

    Parallel stochastic systems biology in the cloud

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    The stochastic modelling of biological systems, coupled with Monte Carlo simulation of models, is an increasingly popular technique in bioinformatics. The simulation-analysis workflow may result computationally expensive redu- cing the interactivity required in the model tuning. In this work, we advocate the high-level software design as a ve- hicle for building efficient and portable parallel simulators for the cloud. In particular, the Calculus of Wrapped Components (CWC) simulator for systems biology, which is designed according to the FastFlow pattern-based approach, is presented and discussed. Thanks to the FastFlow framework, the CWC simulator is designed as a high-level workflow that can simulate CWC models, merge simulation results and statistically analyse them in a single parallel workflow in the cloud. To improve interactivity, successive phases are pipelined in such a way that the workflow begins to output a stream of analysis results immediately after simulation is started. Performance and effectiveness of the CWC simulator are validated on the Amazon Elastic Compute Clou

    PiCo: a novel approach to stream data analytics

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    In this paper, we present a new C++ API with a fluent interface called PiCo (Pipeline Composition). PiCo’s programming model aims at making easier the programming of data analytics applications while preserving or enhancing their performance. This is attained through three key design choices: 1) unifying batch and stream data access models, 2) decoupling processing from data layout, and 3) exploiting a stream-oriented, scalable, efficient C++11 runtime system. PiCo proposes a programming model based on pipelines and operators that are polymorphic with respect to data types in the sense that it is possible to re-use the same algorithms and pipelines on different data models (e.g., streams, lists, sets, etc.). Preliminary results show that PiCo can attain better performances in terms of execution times and hugely improve memory utilization when compared to Spark and Flink in both batch and stream processing.Author's copy (postprint) of C. Misale, M. Drocco, G. Tremblay, and M. Aldinucci, "PiCo: a Novel Approach to Stream Data Analytics," in Proc. of Euro-Par Workshops: 1st Intl. Workshop on Autonomic Solutions for Parallel and Distributed Data Stream Processing (Auto-DaSP 2017), Santiago de Compostela, Spain, 2018. doi:10.1007/978-3-319-75178-8_1
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