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Fig. 6. Vectorial form of the ODE system in a shared memory
number of terms per core, which resulted in a fair balance. The allocation of
terms uses a fine-grained round-robin scheduling.
Since the matrix ˁ is a strongly coupled system, it should be stored in a shared
memory to allow that every core can read the vector ˁ ( i,j ) simultaneously 13 .
6 Experimental Setup
Three models of QDsim were implemented to analyze its performance under
different environments and applying two partition schemes (LP and TP):
- A shared memory model using OpenMP 14
- A distributed memory model using OpenMPI 15
- A hybrid model (distributed/shared memory) using OpenMPI & OpenMP
Basically, these versions tried to answer the following questions:
1. Has a shared memory architecture the same performance as a distributed
memory architecture?
2. Does hyper-threading technology contributes in the computing performance?
13 The simultaneity depends on the size of the level 2 cache and the data size to be
mapped into it.
14 See: http://openmp.org
15 See: http://www.open-mpi.org
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