1,702 research outputs found
An Analysis of Energy Efficient Data Transfer between Mobile Device and Dedicated Server
This paper discusses research results with regard to energy-efficient transmission of serialised data between servers and mobile devices. A test environment was created in which the research authors primarily measured electricity consumption during communication between a mobile device and server. Numerical results were used to determine how well data serialisation was performed on a dedicated server and its effects on the power consumption of a mobile device. The time spent in data serialisation and the size of the serialised file were found to significantly influence energy consumption. Based on that fact, results have been used to create a mathematical model which was later introduced with functional forms. The main variables in those functional forms were time of serialisation and size of a serialised file. The data collected through this research has been used for an experimental API-CB Saver, which based on mathematical models chooses the most favourable manner of serialisation and compression in real time. The results collected during the tests show that the CBSaver-Api approach performs with greater energy efficiency than current techniques. Furthermore, with optimal selection of data serialisation type and compression level in real time the considered system shows better performance in power saving. According to the results, the API-CBSaver tests indicate the direction which one should take for the purposes of improving energy efficiency
Customisable Handling of Java References in Prolog Programs
Integration techniques for combining programs written in distinct language
paradigms facilitate the implementation of specialised modules in the best
language for their task. In the case of Java-Prolog integration, a known
problem is the proper representation of references to Java objects on the
Prolog side. To solve it adequately, multiple dimensions should be considered,
including reference representation, opacity of the representation, identity
preservation, reference life span, and scope of the inter-language conversion
policies. This paper presents an approach that addresses all these dimensions,
generalising and building on existing representation patterns of foreign
references in Prolog, and taking inspiration from similar inter-language
representation techniques found in other domains. Our approach maximises
portability by making few assumptions about the Prolog engine interacting with
Java (e.g., embedded or executed as an external process). We validate our work
by extending JPC, an open-source integration library, with features supporting
our approach. Our JPC library is currently compatible with three different open
source Prolog engines (SWI, YAP} and XSB) by means of drivers. To appear in
Theory and Practice of Logic Programming (TPLP).Comment: 10 pages, 2 figure
Pipelined genetic propagation
© 2015 IEEE.Genetic Algorithms (GAs) are a class of numerical and combinatorial optimisers which are especially useful for solving complex non-linear and non-convex problems. However, the required execution time often limits their application to small-scale or latency-insensitive problems, so techniques to increase the computational efficiency of GAs are needed. FPGA-based acceleration has significant potential for speeding up genetic algorithms, but existing FPGA GAs are limited by the generational approaches inherited from software GAs. Many parts of the generational approach do not map well to hardware, such as the large shared population memory and intrinsic loop-carried dependency. To address this problem, this paper proposes a new hardware-oriented approach to GAs, called Pipelined Genetic Propagation (PGP), which is intrinsically distributed and pipelined. PGP represents a GA solver as a graph of loosely coupled genetic operators, which allows the solution to be scaled to the available resources, and also to dynamically change topology at run-time to explore different solution strategies. Experiments show that pipelined genetic propagation is effective in solving seven different applications. Our PGP design is 5 times faster than a recent FPGA-based GA system, and 90 times faster than a CPU-based GA system
Coping with lists in the ifcOWL ontology
Over the past few years, several suggestions have been made of how to convert an EXPRESS schema into an OWL ontology. The conversion from EXPRESS to OWL is of particular use to architectural design and construction industry, because one of the key data models in architectural design and construction industry, namely the Industry Foundation Classes (IFC) is represented using the EXPRESS information modelling language. In each of these conversion options, the way in which lists are converted (e.g. lists of coordinates, lists of spaces in a floor) is key to the structure and eventual strength of the resulting ontology. In this article, we outline and discuss the main decisions that can be made in converting LIST concepts in EXPRESS to equivalent OWL expressions. This allows one to identify which conversion option is appropriate to support proper and efficient information reuse in the domain of architecture and construction
JIT costing adaptive skeletons for performance portability
The proliferation of widely available, but very different, parallel architectures makes the ability to deliver good parallel performance on a range of architectures, or performance portability, highly desirable. Irregular parallel problems, where the number and size of tasks is unpredictable, are particularly challenging and require dynamic coordination.
The paper outlines a novel approach to delivering portable parallel performance for irregular parallel programs. The approach combines JIT compiler technology with dynamic scheduling and dynamic transformation of declarative parallelism.
We specify families of algorithmic skeletons plus equations for rewriting skeleton expressions. We present the design of a framework that unfolds skeletons into task graphs, dynamically schedules tasks, and dynamically rewrites skeletons, guided by a lightweight JIT trace-based cost model, to adapt the number and granularity of tasks for the architecture.
We outline the system architecture and prototype implementation in Racket/Pycket. As the current prototype does not yet automatically perform dynamic rewriting we present results based on manual offline rewriting, demonstrating that (i) the system scales to hundreds of cores given enough parallelism of suitable granularity, and (ii) the JIT trace cost model predicts granularity accurately enough to guide rewriting towards a good adaptive transformation
Computational statistics using the Bayesian Inference Engine
This paper introduces the Bayesian Inference Engine (BIE), a general
parallel, optimised software package for parameter inference and model
selection. This package is motivated by the analysis needs of modern
astronomical surveys and the need to organise and reuse expensive derived data.
The BIE is the first platform for computational statistics designed explicitly
to enable Bayesian update and model comparison for astronomical problems.
Bayesian update is based on the representation of high-dimensional posterior
distributions using metric-ball-tree based kernel density estimation. Among its
algorithmic offerings, the BIE emphasises hybrid tempered MCMC schemes that
robustly sample multimodal posterior distributions in high-dimensional
parameter spaces. Moreover, the BIE is implements a full persistence or
serialisation system that stores the full byte-level image of the running
inference and previously characterised posterior distributions for later use.
Two new algorithms to compute the marginal likelihood from the posterior
distribution, developed for and implemented in the BIE, enable model comparison
for complex models and data sets. Finally, the BIE was designed to be a
collaborative platform for applying Bayesian methodology to astronomy. It
includes an extensible object-oriented and easily extended framework that
implements every aspect of the Bayesian inference. By providing a variety of
statistical algorithms for all phases of the inference problem, a scientist may
explore a variety of approaches with a single model and data implementation.
Additional technical details and download details are available from
http://www.astro.umass.edu/bie. The BIE is distributed under the GNU GPL.Comment: Resubmitted version. Additional technical details and download
details are available from http://www.astro.umass.edu/bie. The BIE is
distributed under the GNU GP
Fully Homomorphically Encrypted Deep Learning as a Service
Funding: This research was funded by UKRI-EPSRC grant âThe Internet of Food Thingsâ grant number EP/R045127/1.Peer reviewedPublisher PD
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