This paper presents the performance of a set of algorithms written in SISAL [MSA*85] and run on multiprocessor Sequent, DEC, and Cray computers. We describe our current runtime system and discuss its implementation on each machine. We indicate where our automatic approach to parallelization works well, as well as sources of inefficient behavior. Overall we find our systems encouraging for the first release of the native-code generating software. We suggest improvements to the compiler and runtime systems, many already developed but not yet implemented, to alleviate the inefficiencies.
Topic-specific search engines that offered users relevant topics as search results have recently been developed. However, these topic-specific search engines require intensive human efforts to build and maintain. In addition, they visit many irrelevant pages. In our project, we propose a new approach for Web topics search. First, we do early detection for "candidate topics" while extracting words from the HTML text. Secondly, we perform data analysis on the appearance information such as appearance times and places for candidate topics. By these two techniques, we can reduce candidate topics' crawling times and computing cost. Analysis of the results and the comparisons with related research will be made to demonstrate the effectiveness of our approach.
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