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In this paper we introduce a multi-objective auto-tuning framework comprising compiler and runtime components. Focusing on individual code regions, our compiler uses a novel search technique to compute a set of optimal solutions, which are encoded into a multi-versioned executable. This enables the runtime system to choose specifically tuned code versions(More)
Manually tuning MPI runtime parameters is a practice commonly employed to optimise MPI application performance on a specific architecture. However, the best setting for these parameters not only depends on the underlying system but also on the application itself and its input data. This paper introduces a novel approach based on machine learning techniques(More)
Vienna Fortran is a machine-independent language extension of Fortran, which is based upon the Single-Program-Multiple-Data SPMD paradigm and allows the user to write programs for distributed-memory systems using global addresses. The language features focus mainly on the issue of distributing data across virtual processor structures. In this paper, we(More)
A popular interest rate security used by Austrian banks are so called secondary market yield oaters with caps or oors or other types of path dependent embedded options. Since there are no analytical pricing formulas for these constant maturity instruments, numerical techniques have to be employed. In this paper we present Monte Carlo Simulation techniques(More)
In this paper we give an overview of SCALEA, which is a new performance analysis tool for OpenMP, MPI, HPF, and mixed parallel/distributed programs. SCALEA instruments, executes and measures programs and computes a variety of performance overheads based on a novel overhead classification. Source code and HW-profiling is combined in a single system which(More)
There has been an increasing research interest in formalizing and automating the search for performance problems. In previous work we have introduced Aksum, which tries to automatically locate all performance problems in parallel and distributed applications based on multi-experiment performance analysis and user-provided machine and problem sizes. In this(More)
The Aurora nancial management system developed at the University of Vienna is a modular decision support tool for portfolio and asset-liability management. It is based on a multivariate Markovian birth-and-death factor model for the economic environment, a pricing model for the nancial instruments and an objective function which is exible enough to express(More)
Over the last decade, a dramatic increase has been observed in the need for generating and organising data in the course of large parameter studies, performance analysis, and software testing. We have developed the ZENTURIO experiment management tool for performance and parameter studies on cluster and Grid architectures. In this paper we describe our(More)
The Aurora Financial Management System developed at the University of Vienna is a decision support tool for portfolio and asset liability management. An investor chooses a portfolio of various assets or asset classes, in such a way that some objective 9], including a risk measure, is maximized, subject to uncertainty of future markets' development and(More)
Several large real-world applications have been developed for distributed and parallel architectures. We examine two different program development approaches: First, the usage of a high-level programming paradigm which reduces the time to create a parallel program dramatically but sometimes at the cost of a reduced performance. A source-to-source compiler,(More)