A Prolog execution model based on dataflowcomputation is described in terms of the intermediate virtual machine. The virtual machine is operated at clause argument level to exploit argument parallelism through unific...
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A Prolog execution model based on dataflowcomputation is described in terms of the intermediate virtual machine. The virtual machine is operated at clause argument level to exploit argument parallelism through unification. The model utilises a new variable binding scheme that eliminates dereference operations for accessing variables, and therefore simplifies OR-parallel implementation and binding management. A dataflow architecture in support of the model is presented, together with the initial evaluation of the model on the simulated architecture.
Two new processor arrays for the 2D discrete Fourier transform are proposed. Both structural schemes are oriented towards VLSI technology. They can be used in the construction of high-throughput processors for multidi...
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Two new processor arrays for the 2D discrete Fourier transform are proposed. Both structural schemes are oriented towards VLSI technology. They can be used in the construction of high-throughput processors for multidimensional and fast Fourier transforms as well as triple matrix multiplication. The first structural scheme consists of two successively connected one-dimensional arrays of processor elements (PEs), and the second one represents a single array of more complex PEs. The advantages of these structural schemes are the localisation of all data exchanges between PEs and the absence of necessity of matrix transposition.
The Scenario-Aware dataflow (SADF) model is based on concurrent actors that interact via channels. It combines streaming data and control to capture scenarios while incorporating hard and soft real-time aspects. To mo...
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The Scenario-Aware dataflow (SADF) model is based on concurrent actors that interact via channels. It combines streaming data and control to capture scenarios while incorporating hard and soft real-time aspects. To model data-flow computations that are subject to uncertainty, SADF models are equipped with random primitives. We propose to use probabilistic model checking to analyze uncertain SADF models. We show how measures such as expected time, long-run objectives like throughput, as well as timed reachability-can a given system configuration be reached within a deadline with high probability?-can be automatically determined. The crux of our method is a compositional semantics of SADF with exponential agent execution times combined with automated abstraction techniques akin to partial-order reduction. We present the semantics in detail and show how it accommodates the incorporation of execution platforms, enabling the analysis of energy consumption. The feasibility of our approach is illustrated by analyzing several quantitative measures of an MPEG-4 decoder and an industrial face recognition application.
We describe various test selection techniques from Lustre descriptions using the tool GATeL. The Lustre language is declarative and describes synchronous data-flow computations. Our test generation tool interprets the...
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We describe various test selection techniques from Lustre descriptions using the tool GATeL. The Lustre language is declarative and describes synchronous data-flow computations. Our test generation tool interprets the language constructs as boolean and integer interval constraints. Test sequence generation is automated using constraint logic programming techniques. GATeL provides various mechanisms to allow testers to define their own selection strategies. They are illustrated on an simple example.
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