1,721,311 research outputs found
FastFlow parallel programming framework
No full textFastFlow is a C++ parallel programming framework advocating high-level, pattern-based parallel programming. It chiefly supports streaming and data parallelism, targeting heterogenous platforms composed of clusters of shared-memory platforms, possibly equipped with computing accelerators such as GPGPUs, Xeon Phi, Tilera TILE64.The main design philosophy of FastFlow is to provide application designers with key features for parallel programming (e.g. time-to-market, efficiency, functional and performance portability) via suitable parallel programming abstractions and a carefully designed run-time support
SFIDA: interoperability in innovative c-business models for SMEs through an enabling Grid platform
No full textASSIST demo: a High Level, High Performance, Portable, Structured Parallel Programming Environment at Work
No full textProcess-driven biometric identification by means of autonomic grid components
Full text linkToday’s business applications are increasingly process driven, meaning
that the main application logic is executed by a dedicate process engine. In
addition, component-oriented software development has been attracting attention
for building complex distributed applications. In this paper, we present the
experiences gained from building a process-driven biometric identification
application that makes use of grid infrastructures via the Grid Component Model
(GCM). GCM, besides guaranteeing access to grid resources, supports autonomic
management of notable parallel composite components. This feature is exploited
within our biometric identification application to ensure real-time identification of
fingerprints. Therefore, we briefly introduce the GCM framework and the process
engine used, and we describe the implementation of the application by means of
autonomic GCM components. Finally, we summarise the results, experiences and
lessons learned focusing on the integration of autonomic GCM components and
the process-driven approach
Protocol for training MERGE: A federated multi-input neural network for COVID-19 prognosis
No full textFederated learning is a cooperative learning approach that has emerged as an effective way to address privacy concerns. Here, we present a protocol for training MERGE: a federated multi -input neural network (NN) for COVID-19 prognosis. We describe steps for collecting and preprocessing datasets. We then detail the process of training a multi -input NN. This protocol can be adapted for use with datasets containing both image- and table -based input sources. For complete details on the use and execution of this protocol, please refer to Casella et al.
ASSIST as a research framework for high-performance grid programming environments
No full textASSIST (A Software development System based upon Integrated Skeleton
Technology) is a programming environment oriented to the development of parallel
and distributed high-performance applications according to a unified approach. The
language and implementation features of ASSIST are a result of our long-term
research in parallel programming models and tools. ASSIST is evolving towards
programming environments for high-performance complex enabling platforms,
especially Grids. In this paper, we show how ASSIST can act as a valid research
vehicle to study, experiment and realize Grid-aware programming environments for
high-performance applications. Special emphasis is put on the innovative
methodologies, strategies and tools for dynamically adaptive applications, that
represent the necessary step for the success of Grid platforms.
First we discuss the conceptual framework for Grid-aware programming
environments, based upon structured parallel programming and components
technology, anticipating how ASSIST possesses the essential features required by
such framework. Then we summarize the ASSIST programming model, showing its
evolution, along the line of structured parallel programming, to solve critical
problems of expressive power, flexibility, interoperability and efficiency; some
examples, both of kernels and of complex applications, are used to point out the
ASSIST features. The modular compiler model and the current implementation for
heterogeneous platforms and Globus-based Grids are illustrated. We show the
features that allow ASSIST programs to be used in CORBA infrastructures, that
represents our basic starting point towards interoperability in Grid applications.
Finally, the presentation of all the previous issues is used to derive an ASSIST-based
model for supporting dynamically adaptive applications
Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing
Full text linkWe introduce a new parallel pattern derived from a specific application domain and show how it turns out to have application beyond its domain of origin. The pool evolution pattern models the parallel evolution of a population subject to mutations and evolving in such a way that a given fitness function is optimized. The pattern has been demonstrated to be suitable for capturing and modeling the parallel patterns underpinning various evolutionary algorithms, as well as other parallel patterns typical of symbolic computation. In this paper we introduce the pattern, we discuss its implementation on modern multi/many core architectures and finally present experimental results obtained with FastFlow and Erlang implementations to assess its feasibility and scalability.</p
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