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The MOSEK command line tool Version 7.0 (Revision 141)

The MOSEK command line tool. Version 7.0 ... - Documentation

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5.6. SOLVING PROBLEMS IN PARALLEL 47<br />

5.6.2 <strong>The</strong> parallelized interior-point optimizer<br />

<strong>The</strong> interior-point optimizer is capable of using multiple CPUs or cores. This implies that whenever<br />

the <strong>MOSEK</strong> interior-point optimizer solves an optimization problem, it will try to divide the work so<br />

that each core gets a share of the work. <strong>The</strong> user decides how many coress <strong>MOSEK</strong> should exploit.<br />

It is not always possible to divide the work equally, and often parts of the computations and the<br />

coordination of the work is processed sequentially, even if several cores are present. <strong>The</strong>refore, the<br />

speed-up obtained when using multiple cores is highly problem dependent. However, as a rule of<br />

thumb, if the problem solves very quickly, i.e. in less than 60 seconds, it is not advantageous to use<br />

the parallel option.<br />

<strong>The</strong> MSK IPAR NUM THREADS parameter sets the number of threads (and therefore the number of cores)<br />

that the interior point optimizer will use.<br />

5.6.3 <strong>The</strong> concurrent optimizer<br />

An alternative to the parallel interior-point optimizer is the concurrent optimizer. <strong>The</strong> idea of the<br />

concurrent optimizer is to run multiple optimizers on the same problem concurrently, for instance,<br />

it allows you to apply the interior-point and the dual simplex optimizers to a <strong>line</strong>ar optimization<br />

problem concurrently. <strong>The</strong> concurrent optimizer terminates when the first of the applied optimizers<br />

has terminated successfully, and it reports the solution of the fastest optimizer. In that way a new<br />

optimizer has been created which essentially performs as the fastest of the interior-point and the<br />

dual simplex optimizers. Hence, the concurrent optimizer is the best one to use if there are multiple<br />

optimizers available in <strong>MOSEK</strong> for the problem and you cannot say beforehand which one will be<br />

faster.<br />

Note in particular that any solution present in the task will also be used for hot-starting the simplex<br />

algorithms. One possible scenario would therefore be running a hot-start dual simplex in parallel with<br />

interior point, taking advantage of both the stability of the interior-point method and the ability of<br />

the simplex method to use an initial solution.<br />

By setting the<br />

MSK IPAR OPTIMIZER<br />

parameter to<br />

MSK OPTIMIZER CONCURRENT<br />

the concurrent optimizer chosen.<br />

<strong>The</strong> number of optimizers used in parallel is determined by the<br />

MSK IPAR CONCURRENT NUM OPTIMIZERS.<br />

parameter. Moreover, the optimizers are selected according to a preassigned priority with optimizers<br />

having the highest priority being selected first. <strong>The</strong> default priority for each optimizer is shown in<br />

Table 5.6.3. For example, setting the MSK IPAR CONCURRENT NUM OPTIMIZERS parameter to 2 tells the<br />

concurrent optimizer to the apply the two optimizers with highest priorities: In the default case that<br />

means the interior-point optimizer and one of the simplex optimizers.

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