83,372 research outputs found
Using Cognitive Computing for Learning Parallel Programming: An IBM Watson Solution
While modern parallel computing systems provide high performance resources,
utilizing them to the highest extent requires advanced programming expertise.
Programming for parallel computing systems is much more difficult than
programming for sequential systems. OpenMP is an extension of C++ programming
language that enables to express parallelism using compiler directives. While
OpenMP alleviates parallel programming by reducing the lines of code that the
programmer needs to write, deciding how and when to use these compiler
directives is up to the programmer. Novice programmers may make mistakes that
may lead to performance degradation or unexpected program behavior. Cognitive
computing has shown impressive results in various domains, such as health or
marketing. In this paper, we describe the use of IBM Watson cognitive system
for education of novice parallel programmers. Using the dialogue service of the
IBM Watson we have developed a solution that assists the programmer in avoiding
common OpenMP mistakes. To evaluate our approach we have conducted a survey
with a number of novice parallel programmers at the Linnaeus University, and
obtained encouraging results with respect to usefulness of our approach
Modeling adaptation with a tuple-based coordination language
In recent years, it has been argued that systems and applications, in order to deal with their increasing complexity, should be able to adapt their behavior according to new requirements or environment conditions. In this paper, we present a preliminary investigation aiming at studying how coordination languages and formal methods can contribute to a better understanding, implementation and usage of the mechanisms and techniques for adaptation currently proposed in the literature. Our study relies on the formal coordination language Klaim as a common framework for modeling some adaptation techniques, namely the MAPE-K loop, aspect- and context-oriented programming
Toward a Formal Semantics for Autonomic Components
Autonomic management can improve the QoS provided by parallel/ distributed
applications. Within the CoreGRID Component Model, the autonomic management is
tailored to the automatic - monitoring-driven - alteration of the component
assembly and, therefore, is defined as the effect of (distributed) management
code. This work yields a semantics based on hypergraph rewriting suitable to
model the dynamic evolution and non-functional aspects of Service Oriented
Architectures and component-based autonomic applications. In this regard, our
main goal is to provide a formal description of adaptation operations that are
typically only informally specified. We contend that our approach makes easier
to raise the level of abstraction of management code in autonomic and adaptive
applications.Comment: 11 pages + cover pag
Jeeva: Enterprise Grid-enabled Web Portal for Protein Secondary Structure Prediction
This paper presents a Grid portal for protein secondary structure prediction
developed by using services of Aneka, a .NET-based enterprise Grid technology.
The portal is used by research scientists to discover new prediction structures
in a parallel manner. An SVM (Support Vector Machine)-based prediction
algorithm is used with 64 sample protein sequences as a case study to
demonstrate the potential of enterprise Grids.Comment: 7 page
Porting Decision Tree Algorithms to Multicore using FastFlow
The whole computer hardware industry embraced multicores. For these machines,
the extreme optimisation of sequential algorithms is no longer sufficient to
squeeze the real machine power, which can be only exploited via thread-level
parallelism. Decision tree algorithms exhibit natural concurrency that makes
them suitable to be parallelised. This paper presents an approach for
easy-yet-efficient porting of an implementation of the C4.5 algorithm on
multicores. The parallel porting requires minimal changes to the original
sequential code, and it is able to exploit up to 7X speedup on an Intel
dual-quad core machine.Comment: 18 pages + cove
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