87,147 research outputs found
ARGOS policy brief on semantic interoperability
Semantic interoperability requires the use of standards, not only for Electronic Health Record (EHR) data to be transferred and structurally mapped into a receiving repository, but also for the clinical content of the EHR to be interpreted in conformity with the original meanings intended by its authors. Accurate and complete clinical documentation, faithful to the patient’s situation, and interoperability between systems, require widespread and dependable access to published and maintained collections of coherent and quality-assured semantic resources, including models such as archetypes and templates that would (1) provide clinical context, (2) be mapped to interoperability standards for EHR data, (3) be linked to well specified, multi-lingual terminology value sets, and (4) be derived from high quality ontologies. Wide-scale engagement with professional bodies, globally, is needed to develop these clinical information standards
Formal Aspects of Grid Brokering
Coordination in distributed environments, like Grids, involves selecting the
most appropriate services, resources or compositions to carry out the planned
activities. Such functionalities appear at various levels of the infrastructure
and in various means forming a blurry domain, where it is hard to see how the
participating components are related and what their relevant properties are. In
this paper we focus on a subset of these problems: resource brokering in Grid
middleware. This paper aims at establishing a semantical model for brokering
and related activities by defining brokering agents at three levels of the Grid
middleware for resource, host and broker selection. The main contribution of
this paper is the definition and decomposition of different brokering
components in Grids by providing a formal model using Abstract State Machines
Exact Gap Computation for Code Coverage Metrics in ISO-C
Test generation and test data selection are difficult tasks for model based
testing. Tests for a program can be meld to a test suite. A lot of research is
done to quantify the quality and improve a test suite. Code coverage metrics
estimate the quality of a test suite. This quality is fine, if the code
coverage value is high or 100%. Unfortunately it might be impossible to achieve
100% code coverage because of dead code for example. There is a gap between the
feasible and theoretical maximal possible code coverage value. Our review of
the research indicates, none of current research is concerned with exact gap
computation. This paper presents a framework to compute such gaps exactly in an
ISO-C compatible semantic and similar languages. We describe an efficient
approximation of the gap in all the other cases. Thus, a tester can decide if
more tests might be able or necessary to achieve better coverage.Comment: In Proceedings MBT 2012, arXiv:1202.582
AutoAccel: Automated Accelerator Generation and Optimization with Composable, Parallel and Pipeline Architecture
CPU-FPGA heterogeneous architectures are attracting ever-increasing attention
in an attempt to advance computational capabilities and energy efficiency in
today's datacenters. These architectures provide programmers with the ability
to reprogram the FPGAs for flexible acceleration of many workloads.
Nonetheless, this advantage is often overshadowed by the poor programmability
of FPGAs whose programming is conventionally a RTL design practice. Although
recent advances in high-level synthesis (HLS) significantly improve the FPGA
programmability, it still leaves programmers facing the challenge of
identifying the optimal design configuration in a tremendous design space.
This paper aims to address this challenge and pave the path from software
programs towards high-quality FPGA accelerators. Specifically, we first propose
the composable, parallel and pipeline (CPP) microarchitecture as a template of
accelerator designs. Such a well-defined template is able to support efficient
accelerator designs for a broad class of computation kernels, and more
importantly, drastically reduce the design space. Also, we introduce an
analytical model to capture the performance and resource trade-offs among
different design configurations of the CPP microarchitecture, which lays the
foundation for fast design space exploration. On top of the CPP
microarchitecture and its analytical model, we develop the AutoAccel framework
to make the entire accelerator generation automated. AutoAccel accepts a
software program as an input and performs a series of code transformations
based on the result of the analytical-model-based design space exploration to
construct the desired CPP microarchitecture. Our experiments show that the
AutoAccel-generated accelerators outperform their corresponding software
implementations by an average of 72x for a broad class of computation kernels
A Comparison of Big Data Frameworks on a Layered Dataflow Model
In the world of Big Data analytics, there is a series of tools aiming at
simplifying programming applications to be executed on clusters. Although each
tool claims to provide better programming, data and execution models, for which
only informal (and often confusing) semantics is generally provided, all share
a common underlying model, namely, the Dataflow model. The Dataflow model we
propose shows how various tools share the same expressiveness at different
levels of abstraction. The contribution of this work is twofold: first, we show
that the proposed model is (at least) as general as existing batch and
streaming frameworks (e.g., Spark, Flink, Storm), thus making it easier to
understand high-level data-processing applications written in such frameworks.
Second, we provide a layered model that can represent tools and applications
following the Dataflow paradigm and we show how the analyzed tools fit in each
level.Comment: 19 pages, 6 figures, 2 tables, In Proc. of the 9th Intl Symposium on
High-Level Parallel Programming and Applications (HLPP), July 4-5 2016,
Muenster, German
Approaches to Semantic Web Services: An Overview and Comparison
Abstract. The next Web generation promises to deliver Semantic Web Services (SWS); services that are self-described and amenable to automated discovery, composition and invocation. A prerequisite to this, however, is the emergence and evolution of the Semantic Web, which provides the infrastructure for the semantic interoperability of Web Services. Web Services will be augmented with rich formal descriptions of their capabilities, such that they can be utilized by applications or other services without human assistance or highly constrained agreements on interfaces or protocols. Thus, Semantic Web Services have the potential to change the way knowledge and business services are consumed and provided on the Web. In this paper, we survey the state of the art of current enabling technologies for Semantic Web Services. In addition, we characterize the infrastructure of Semantic Web Services along three orthogonal dimensions: activities, architecture and service ontology. Further, we examine and contrast three current approaches to SWS according to the proposed dimensions
Specifying Reusable Components
Reusable software components need expressive specifications. This paper
outlines a rigorous foundation to model-based contracts, a method to equip
classes with strong contracts that support accurate design, implementation, and
formal verification of reusable components. Model-based contracts
conservatively extend the classic Design by Contract with a notion of model,
which underpins the precise definitions of such concepts as abstract
equivalence and specification completeness. Experiments applying model-based
contracts to libraries of data structures suggest that the method enables
accurate specification of practical software
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