Experience with a vectorized general circulation weather model on Star-100

A version of an atmospheric general circulation model was vectorized to run on a CDC STAR 100. The numerical model was coded and run in two different vector languages, CDC and LRLTRAN. A factor of 10 speed improvement over an IBM 360/95 was realized. Efficient use of the STAR machine required some redesigning of algorithms and logic. This precludes the application of vectorizing compilers on the original scalar code to achieve the same results. Vector languages permit a more natural and efficient formulation for such numerical codes

Analyzing logic programs with dynamic scheduling

Traditional logic programming languages, such as Prolog, use a fixed left-to-right atom scheduling rule. Recent logic programming languages, however, usually provide more flexible scheduling in which computation generally proceeds leftto- right but in which some calis are dynamically "delayed" until their arguments are sufRciently instantiated to allow the cali to run efficiently. Such dynamic scheduling has a significant cost. We give a framework for the global analysis of logic programming languages with dynamic scheduling and show that program analysis based on this framework supports optimizations which remove much of the overhead of dynamic scheduling

CPL: A Core Language for Cloud Computing -- Technical Report

Running distributed applications in the cloud involves deployment. That is, distribution and configuration of application services and middleware infrastructure. The considerable complexity of these tasks resulted in the emergence of declarative JSON-based domain-specific deployment languages to develop deployment programs. However, existing deployment programs unsafely compose artifacts written in different languages, leading to bugs that are hard to detect before run time. Furthermore, deployment languages do not provide extension points for custom implementations of existing cloud services such as application-specific load balancing policies. To address these shortcomings, we propose CPL (Cloud Platform Language), a statically-typed core language for programming both distributed applications as well as their deployment on a cloud platform. In CPL, application services and deployment programs interact through statically typed, extensible interfaces, and an application can trigger further deployment at run time. We provide a formal semantics of CPL and demonstrate that it enables type-safe, composable and extensible libraries of service combinators, such as load balancing and fault tolerance.Comment: Technical report accompanying the MODULARITY '16 submissio

Achieving QVTO & ATL Interoperability: An Experience Report on the Realization of a QVTO to ATL Computer

With the emergence of a number of model transformation languages the need for interoperability among them increases. The degree at which this interoperability can be achieved between two given languages depends heavily on their paradigms (declarative vs imperative). Previous studies have indicated that the QVT and ATL languages are compatible. In this paper we study the possibility to compile QVT Operational to the ATL virtual machine. We describe our experience of developing such a compiler. The resulting compiled QVT transformations can run on top of existing ATL tools. Thereby we achieve not only QVT/ATL interoperability but also QVT conformance for the ATL tools as defined in the QVT specification

Self-Similar Algebras with connections to Run-length Encoding and Rational Languages

A self-similar algebra $\left(\mathfrak{A}, \psi \right)$ is an associative algebra $\mathfrak{A}$ with a morphism of algebras $\psi: \mathfrak{A} \longrightarrow M_d \left( \mathfrak{A}\right)$, where $M_d \left( \mathfrak{A}\right)$ is the set of $d\times d$ matrices with coefficients from $\mathfrak{A}$. We study the connection between self-similar algebras with run-length encoding and rational languages. In particular, we provide a curious relationship between the eigenvalues of a sequence of matrices related to a specific self-similar algebra and the smooth words over a 2-letter alphabet. We also consider the language $L(s)$ of words $u$ in $(\Sigma\times \Sigma)^*$ where $\Sigma=\{0,1\}$ such that $s\cdot u$ is a unit in $\mathfrak{A}$. We prove that $L(s)$ is rational and provide an asymptotic formula for the number of words of a given length in $L(s)$

XMILE:An XML-based approach for programmable networks

In this paper we describe an XML-based platform for dynamic active node policy updates. XML supports the definitionof specific policy languages, their extension to satisfy new needs and the management of deployed policies on differentactive nodes. We show an example of the management of router packet forwarding policies where the XML policiesthat drive the packet routing are updated at run-time on the active nodes depending on the network status. The platformdecouples policy management, which is handled through XML interpretation, from packet forwarding that, forperformance reasons has to be implemented in more efficient languages

Cross-Lingual Induction and Transfer of Verb Classes Based on Word Vector Space Specialisation

Existing approaches to automatic VerbNet-style verb classification are heavily dependent on feature engineering and therefore limited to languages with mature NLP pipelines. In this work, we propose a novel cross-lingual transfer method for inducing VerbNets for multiple languages. To the best of our knowledge, this is the first study which demonstrates how the architectures for learning word embeddings can be applied to this challenging syntactic-semantic task. Our method uses cross-lingual translation pairs to tie each of the six target languages into a bilingual vector space with English, jointly specialising the representations to encode the relational information from English VerbNet. A standard clustering algorithm is then run on top of the VerbNet-specialised representations, using vector dimensions as features for learning verb classes. Our results show that the proposed cross-lingual transfer approach sets new state-of-the-art verb classification performance across all six target languages explored in this work.Comment: EMNLP 2017 (long paper

Mean-payoff Automaton Expressions

Quantitative languages are an extension of boolean languages that assign to each word a real number. Mean-payoff automata are finite automata with numerical weights on transitions that assign to each infinite path the long-run average of the transition weights. When the mode of branching of the automaton is deterministic, nondeterministic, or alternating, the corresponding class of quantitative languages is not robust as it is not closed under the pointwise operations of max, min, sum, and numerical complement. Nondeterministic and alternating mean-payoff automata are not decidable either, as the quantitative generalization of the problems of universality and language inclusion is undecidable. We introduce a new class of quantitative languages, defined by mean-payoff automaton expressions, which is robust and decidable: it is closed under the four pointwise operations, and we show that all decision problems are decidable for this class. Mean-payoff automaton expressions subsume deterministic mean-payoff automata, and we show that they have expressive power incomparable to nondeterministic and alternating mean-payoff automata. We also present for the first time an algorithm to compute distance between two quantitative languages, and in our case the quantitative languages are given as mean-payoff automaton expressions

The psychological reality of rhythm classes: Perceptual studies

Linguists have traditionally classified languages into three rhythm classes, namely stress-timed, syllable-timed and mora-timed languages. However, this classification has remained controversial for various reasons: the search for reliable acoustic cues to the different rhythm types has long remained elusive; some languages are claimed to belong to none of the three classes; and few perceptual studies has bolstered the notion. We have previously proposed an acoustic/phonetic model of the different types of linguistic rhythm, and of their categorisation as such by listeners. Here, we present perceptual experiments that directly test the notion of rhythm classes, our model's predictions, and the question of intermediate languages. Language discrimination experiments were run using a speech resynthesis technique to ensure that only rhythmic cues were available to the subjects. Languages investigated were English, Dutch, Spanish, Catalan and Polish. Our results are consistent with the idea that English and Dutch are stress-timed, Spanish and Catalan are syllable-timed, but Polish seems to be different from any other language studied and thus may constitute a new rhythm class. We propose that perceptual studies tapping the ability to discriminate languages' rhythm are the proper way to generate more empirical data relevant to rhythm typology