The purpose of this paper is to estimate the cost of utilizing under populated, or sparse, networks on chip (NOC) for chip multiprocessors (CMP). In under-populated NOCs, only a portion of nodes are sources and sinks whereas the rest are simple intermediate nodes increasing communication bandwidth. Compared to dense NOCs, where all nodes can be sources and sinks of communication, the under populated NOCs can be scaled so that any degree of communication frequency of nodes can be supported. The drawback of under populated NOCs is larger network area and bigger logical diameter. GPGPU-style stream-based or high-throughput CMPs can be used to hide the effect of longer latencies. In this paper, we present layouts for mesh-based under populated networks, calculate their wire length distributions and the overall area. Moreover, we present energy consumption calculations for such networks, and show that while the network part of a CMP system based on under populated NOCs can play a major role when considering the chip area and energy consumption, it can be pushed down by increasing the number of dimensions and using meshes instead of tori. We also compare various multidimensional sparse mesh-layouts and conclude the 3-dimensional and 4-dimensional sparse meshes to be the most attractive ones for throughput computing.

In this paper we develop a syntax-directed approach to transformation of documents from one structure to another. The aim is to automate a transformation between two grammars that have common parts, although the grammars and names of elements may differ. In an important case, called local transformations, the transformation can be performed by a finite state tree transducer. We propose a system that can generate a transformation semi-automatically if the user defines a matching between the elements containing the text of the document. Multiple possible translations from the target grammar can be restricted using a suitable heuristic function so that the transformation can be completed in a reasonable time period. From the generated transformation specification, it is possible to construct rules for a tree transducer or XSLT script automatically.

The purpose of a model of computation is to provide the algorithm designer a device for running algorithms. It should be conceptually clear to let him or her concentrate at the algorithmic ideas for solving the problem. At the same time it should be

We prove that a $T(n)$ time-bounded, $S(n)$ space-bounded and $U(n)$ output-length-bounded Turing machine can be simulated in $O(T(n) + (n + U(n))\log \log S(n))$ time by a random access machine (with no multiplication or division instructions) under the logarithmic cost criterion.

Abstract Parsing can be applied to compress source programs. A suitably encoded parse tree, together with the symbol table, constitutes a very compact representation of the program. The paper reports a Prolog implementation of the method, including automatic, syntax‐directed, encoder and decoder generators. The test results show compression gains of 50–60 per cent.