FooPar: A Functional Object Oriented Parallel Framework in Scala

We present FooPar, an extension for highly efficient Parallel Computing in the multi-paradigm programming language Scala. Scala offers concise and clean syntax and integrates functional programming features. Our framework FooPar combines these features with parallel computing techniques. FooPar is designed modular and supports easy access to different communication backends for distributed memory architectures as well as high performance math libraries. In this article we use it to parallelize matrix matrix multiplication and show its scalability by a isoefficiency analysis. In addition, results based on a empirical analysis on two supercomputers are given. We achieve close-to-optimal performance wrt. theoretical peak performance. Based on this result we conclude that FooPar allows to fully access Scala's design features without suffering from performance drops when compared to implementations purely based on C and MPI

Reliable scalable symbolic computation: The design of SymGridPar2

Symbolic computation is an important area of both Mathematics and Computer Science, with many large computations that would benefit from parallel execution. Symbolic computations are, however, challenging to parallelise as they have complex data and control structures, and both dynamic and highly irregular parallelism. The SymGridPar framework (SGP) has been developed to address these challenges on small-scale parallel architectures. However the multicore revolution means that the number of cores and the number of failures are growing exponentially, and that the communication topology is becoming increasingly complex. Hence an improved parallel symbolic computation framework is required. This paper presents the design and initial evaluation of SymGridPar2 (SGP2), a successor to SymGridPar that is designed to provide scalability onto 10^5 cores, and hence also provide fault tolerance. We present the SGP2 design goals, principles and architecture. We describe how scalability is achieved using layering and by allowing the programmer to control task placement. We outline how fault tolerance is provided by supervising remote computations, and outline higher-level fault tolerance abstractions. We describe the SGP2 implementation status and development plans. We report the scalability and efficiency, including weak scaling to about 32,000 cores, and investigate the overheads of tolerating faults for simple symbolic computations

Rewriting and narrowing for constructor systems with call-time choice semantics

Non-confluent and non-terminating constructor-based term rewrite systems are useful for the purpose of specification and programming. In particular, existing functional logic languages use such kind of rewrite systems to define possibly non-strict non-deterministic functions. The semantics adopted for non-determinism is call-time choice, whose combination with non-strictness is a non trivial issue, addressed years ago from a semantic point of view with the Constructor-based Rewriting Logic (CRWL), a well-known semantic framework commonly accepted as suitable semantic basis of modern functional logic languages. A drawback of CRWL is that it does not come with a proper notion of one-step reduction, which would be very useful to understand and reason about how computations proceed. In this paper we develop thoroughly the theory for the first order version of letrewriting, a simple reduction notion close to that of classical term rewriting, but extended with a let-binding construction to adequately express the combination of call-time choice with non-strict semantics. Let-rewriting can be seen as a particular textual presentation of term graph rewriting. We investigate the properties of let-rewriting, most remarkably their equivalence with respect to a conservative extension of the CRWL-semantics coping with let-bindings, and we show by some case studies that having two interchangeable formal views (reduction/semantics) of the same language is a powerful reasoning tool. After that, we provide a notion of let-narrowing which is adequate for call-time choice as proved by soundness and completeness results of let-narrowing with respect to letre writing. Moreover, we relate those let-rewriting and let-narrowing relations (and hence CRWL) with ordinary term rewriting and narrowing, providing in particular soundness and completeness of let-rewriting with respect to term rewriting for a class of programs which are deterministic in a semantic sense

Basic completion strategies as another application of the Maude strategy language

The two levels of data and actions on those data provided by the separation between equations and rules in rewriting logic are completed by a third level of strategies to control the application of those actions. This level is implemented on top of Maude as a strategy language, which has been successfully used in a wide range of applications. First we summarize the Maude strategy language design and review some of its applications; then, we describe a new case study, namely the description of completion procedures as transition rules + control, as proposed by Lescanne.Comment: In Proceedings WRS 2011, arXiv:1204.531

Visualization of transcoronary ablation of septal hypertrophy in patients with hypertrophic obstructive cardiomyopathy: a comparison between cardiac MRI, invasive measurements and echocardiography

Hypertrophic obstructive cardiomyopathy (HOCM) is treated by surgical myectomy or transcoronary ablation of septal hypertrophy (TASH). The aim of this study was to visualize the feasibility, success and short-term results of TASH on the basis of cardiac MRI (CMR) in comparison with cardiac catheterization and echocardiography. In this in vivo study, nine patients with HOCM were treated with TASH. Patients were evaluated by transthoracic echocardiography, invasive cardiac angiography and CMR. Follow-up examinations were carried out after 1, 3 and 12 months. MR imaging was performed on a 1.5-T scanner. All images were processed using the semiautomatic Argus software and were evaluated by an attending thoracic radiologist and cardiologist. The echocardiographic pressure gradient (at rest) was 69.3 +/- A 15.3 mmHg before and 22.1 +/- A 5.7 mmHg after TASH (P < 0.01, n = 9). The flux acceleration over the aortic valve examined (V (max)) was 5.1 +/- A 0.6 m/s before and 3.4 +/- A 0.3 m/s after the TASH procedure (P < 0.05). Also, there was a decrease of septum thickness from 22.0 +/- A 1.2 to 20.2 +/- A 1.0 mm (P < 0.05) after 6 +/- A 3 weeks. The invasively assessed pressure gradient at rest was reduced from 63.7 +/- A 15.2 to 21.2 +/- A 11.1 mmHg (P < 0.01) and the post-extrasystolic gradient was reduced from 138.9 +/- A 12.7 to 45.6 +/- A 16.5 mmHg (P < 0.01). All differences as well as the quantity of injected ethanol were plotted against the size or amount of scar tissue as assessed in the MRI. There was a statistically significant correlation between the post-extrasystolic gradient decrease and the amount of scar tissue (P = 0.03, r (2) = 0.5). In addition, the correlation between the quantity of ethanol and scar tissue area was highly significant (P < 0.01, r (2) = 0.6), whereas the values for the gradient deviation (P = 0.10, r (2) = 0.34), Delta V (max) (P = 0.12, r (2) = 0.31), as well as the gradient at rest (P = 0.27, r (2) = 0.17) were not significant. TASH was consistently effective in reducing the gradient in all patients with HOCM. In contrast to the variables investigated by echocardiography, the invasively measured post-extrasystolic gradient correlated much better with the amount of scar tissue as assessed by CMR. We conclude that the optimal modality to visualize the TASH effect seems to be a combination of CMR and the invasive identification of the post-extrasystolic gradient.Deutsche Forschungsgemeinschaft (DFG) [MA 1982/2-2, MA 1982/4-1

Towards Applying River Formation Dynamics in Continuous Optimization Problems

River Formation Dynamics (RFD) is a metaheuristic that has been successfully used by different research groups to deal with a wide variety of discrete combinatorial optimization problems. However, no attempt has been done to adapt it to continuous optimization domains. In this paper we propose a first approach to obtain such objective, and we evaluate its usefulness by comparing RFD results against those obtained by other more mature metaheuristics for continuous domains. In particular, we compare with the results obtained by Particle Swarm Optimization, Artificial Bee Colony, Firefly Algorithm, and Social Spider Optimization