Languages and Compilers for Parallel Computing: 13th by Francisco Corbera, Rafael Asenjo, Emilio Zapata (auth.),

By Francisco Corbera, Rafael Asenjo, Emilio Zapata (auth.), Samuel P. Midkiff, José E. Moreira, Manish Gupta, Siddhartha Chatterjee, Jeanne Ferrante, Jan Prins, William Pugh, Chau-Wen Tseng (eds.)

This quantity includes the papers offered on the thirteenth overseas Workshop on Languages and Compilers for Parallel Computing. It additionally comprises prolonged abstracts of submissions that have been authorised as posters. The workshop used to be held on the IBM T. J. Watson study middle in Yorktown Heights, ny. As in past years, the workshop considering matters in optimizing compilers, languages, and software program environments for prime functionality computing. This maintains a pattern during which languages, compilers, and software program environments for top functionality computing, and never strictly parallel computing, has been the organizing subject. As in prior years, contributors got here from Asia, North the US, and Europe. This workshop re?ected the paintings of many folks. particularly, the participants of the guidance committee, David Padua, Alex Nicolau, Utpal Banerjee, and David Gelernter, were instrumental in retaining the point of interest and caliber of the workshop because it used to be ?rst held in 1988 in Urbana-Champaign. the help of the opposite contributors of this system committee – Larry Carter, Sid Chatterjee, Jeanne Ferrante, Jans Prins, invoice Pugh, and Chau-wen Tseng – used to be an important. The infrastructure on the IBM T. J. Watson examine middle supplied simple logistical help. The IBM T. J. Watson study heart additionally supplied ?nancial help through underwriting a lot of the rate of the workshop. Appreciation also needs to be prolonged to Marc Snir and Pratap Pattnaik of the IBM T. J. Watson learn heart for his or her support.

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Extra resources for Languages and Compilers for Parallel Computing: 13th International Workshop, LCPC 2000 Yorktown Heights, NY, USA, August 10–12, 2000 Revised Papers

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Thus the notation READ bi := Xi means that a PRAM READ operation is performed with f and g functions defined so as to perform the parallel assignment. Similar conventions are used for the other operations, EXECUTE and WRITE. Furthermore, a constraint on the value of i in an operation means that the operation is performed only in those sites where the constraint is satisfied; other sites do nothing. ) Figure 4 (left) gives the program realizing the multiprefix operation [2]. The algorithm first copies the array X into Y .

However, it is not enough just to keep the semantics of the APM parallel operations and their costs: the APM definitions are still needed, as they make explicit the organization of data and computation into sites. Efficient algorithm design for parallel machines must consider not only when an computation on data is performed, but also where. An example is programming on a distributed memory machine where a poorly chosen distribution of data to sites may cause time-consuming communication. We therefore conclude that all three components of the methodology are essential, but they should be separated from each other and made distinct.

Each processor is similar to a RAM that can access its local random access memory and the common memory. , all processors needed in the algorithm take part in a number of consecutive synchronized computation steps in which the same local function is performed. One PRAM step consists of three parts: 1. the processors read from the common memory; 2. the processors perform local computation with data from their local memories; and 3. the processors write results to the common memory. Local computations differ because of the local data used and the unique identification number id i of each processor Pi , for i = 1, .

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