Parallel Programming: for Multicore and Cluster Systems- P33 ppt

Parallel Programming: for Multicore and Cluster Systems- P33 ppt

Parallel Programming: for Multicore and Cluster Systems- P33 ppt

... a.swapBalance(b) and locks the mutex variable of object a; • time T 2 : thread A calls getBalance() for object a and executes this function; • time T 2 : thread B calls b.swapBalance(a) and locks the ... pthread - cond wait() and pthread cond signal() for condition variables in Pthreads, see Sect. 6.1.3, p. 270. The methods wait() and notify() are imple- mented using an implicit...

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Parallel Programming: for Multicore and Cluster Systems- P4 pptx

Parallel Programming: for Multicore and Cluster Systems- P4 pptx

... separate thread available for execution. Therefore, the application program must apply parallel pro- gramming techniques to get performance improvements for SMT processors. 2.4.2 MulticoreProcessors According ... be used for the transmission and the switching strategy which determines whether and how mes- sages are cut into pieces, how a routing path is assigned to a message, and...

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Parallel Programming: for Multicore and Cluster Systems- P13 ppt

Parallel Programming: for Multicore and Cluster Systems- P13 ppt

... Pthreads and Sect. 6.2.3 for Java threads. 114 3 Parallel Programming Models j, j + p, , j + p · ( n/p−1 ) for j ≤ n mod p and j, j + p, , j + p · ( n/p−2 ) for n mod p < j ≤ p. For the ... partitioning. In a parallel program, the processors perform computations only on their part of the data. Data distributions can be used for parallel programs for distributed as...

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Parallel Programming: for Multicore and Cluster Systems- P14 ppt

Parallel Programming: for Multicore and Cluster Systems- P14 ppt

... are no dependencies and the loops over i and j can be exchanged. For a parallel implementation, the row- and column-oriented representations of matrix A give rise to different parallel imple- mentation ... b, and c for the program given in Fig. 3.10. For a row-oriented cyclic distribution, each processor P k , k = 1, , p,stores the rows a i of matrix A with i = k + p ·(l − 1...

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Parallel Programming: for Multicore and Cluster Systems- P21 pptx

Parallel Programming: for Multicore and Cluster Systems- P21 pptx

... Language bindings for C, C++, Fortran-77, and Fortran-95 are sup- ported. In the following, we concentrate on the interface for C and describe the most important features. For a detailed description, ... product and a matrix–vector multiplication and derive the formula for the running time on a mesh topology. Exercise 4.14 Develop a runtime function to capture the execution ti...

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Parallel Programming: for Multicore and Cluster Systems- P25 pptx

Parallel Programming: for Multicore and Cluster Systems- P25 pptx

... communication partners in the form source/dest are given in this order. For example, for the process with rank=5,itiscoords[1]=1, and there- fore source=9 (lower neighbor in dimension 0) and dest=1 (upper ... and source for each pro- cess. These are then used as parameters for MPI Sendrecv(). The following diagram illustrates the exchange. For each process, its rank, its Carte...

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Parallel Programming: for Multicore and Cluster Systems- P34 ppt

Parallel Programming: for Multicore and Cluster Systems- P34 ppt

... wait() and notify(). This is shown in Fig. 6.35 for a class Barrier, see also [129]. The Barrier class contains a constructor which initializes a Barrier object with the number of threads to wait for ... shown in Fig. 6.39 can be used for the synchro- nization of producer and consumer threads. A similar mechanism has already been implemented in Fig. 6.32 by using wait() and notify...

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