{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T14:31:57Z","timestamp":1676644317137},"reference-count":26,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Parallel Process. Lett."],"published-print":{"date-parts":[[2005,9]]},"abstract":"<jats:p> Performance programming is characterized by the need to structure software components to exploit the context of use. Relevant context includes the target processor architecture, the available resources (number of processors, network capacity), prevailing resource contention, the values and shapes of input and intermediate data structures, the schedule and distribution of input data delivery, and the way the results are to be used. This paper concerns adapting to dynamic context: adaptive algorithms, malleable and migrating tasks, and application structures based on dynamic component composition. Adaptive computations use metadata associated with software components \u2014 performance models, dependence information, data size and shape. Computation itself is interwoven with planning and optimizing the computation process, using this metadata. This reflective nature motivates metaprogramming techniques. We present a research agenda aimed at developing a modelling framework which allows us to characterize both computation and dynamic adaptation in a way that allows systematic optimization. <\/jats:p>","DOI":"10.1142\/s0129626405002192","type":"journal-article","created":{"date-parts":[[2005,9,13]],"date-time":"2005-09-13T21:21:12Z","timestamp":1126646472000},"page":"239-255","source":"Crossref","is-referenced-by-count":4,"title":["GENERATIVE AND ADAPTIVE METHODS IN PERFORMANCE PROGRAMMING"],"prefix":"10.1142","volume":"15","author":[{"given":"PAUL H. J.","family":"KELLY","sequence":"first","affiliation":[{"name":"Department of Computing,  Imperial College of Science, Technology and Medicine,  180 Queen's Gate, London SW7 2AZ, United Kingdom"}]},{"given":"OLAV","family":"BECKMANN","sequence":"additional","affiliation":[{"name":"Department of Computing,  Imperial College of Science, Technology and Medicine,  180 Queen's Gate, London SW7 2AZ, United Kingdom"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","series-title":"LNCS 2400","volume-title":"Euro-Par 2002","author":"Field A. 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