Matthias Besch

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Implementing realistic scientific applications on parallel platforms requires a high–level, problem–adequate and flexible programming environment. The hybrid system PROMOTER pursues a two–level approach allowing easy and flexible programming at both language and library levels. The core concept of PROMOTER’s language model is its highly abstract and unified(More)
Mapping is regarded as one of the core components of parallel computing environments on various platforms, and influences to a large extent the runtime performance of a parallel application. To be efficient, mapping algorithms must be able to exploit as much as possible high-level information about spatial and temporal structures that occur in an(More)
Structured, dependence-free decomposition of aggregate data objects can be regarded as a generalized form of classical array alignment and addresses the problem of finding the maximum amount of independent computation on nonconnected data sets. The paper presents a unified concept for modelling both data spaces and affine dependence relations with the help(More)
Dependence-free clustering of data structures can be regarded as a general form of alignment and addresses the problem of finding the maximum amount of independent computation on non-connected data sets. The paper presents a unified concept for modelling both data spaces and affine dependence relations with the help of Abelian subgroups of Z, n. This(More)
A key issue of problem-oriented parallel programming is an appropriate concept for representing the spatial structures of an application and modelling local or global interactions operating on them. This paper advocates for the use of so-called index spaces as a unified and powerful expression tool. It discusses the interface between application modelling(More)
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