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The table of speeds up that can be achieved based on a serial algorithm in the parallel world is shown below. The table shows that in the parallel world, if we have a problem with average p parallel fraction, which can be defined as the fraction of the runtime that is spent on the parallel portion of the algorithm, the number of parallel processors can be calculated from the speedup formula as N = 1/s + p.
When a program is converted to a parallel version, it is important to identify the different types of parallelism that can be exploited in order to get the optimal performance. A serial application might have been designed to use a particular type of parallelism that is not suitable for a parallel computer. Two parallel algorithms in the same code could be analyzed to determine which one performs better for the parallel computer hardware.
The MATLAB environment is based on the MathWorks MATLAB® Compiler, or MMC, which is a proprietary language developed by MathWorks to facilitate the building of applications. MMC understands the MATLAB language and various task APIs and provides efficient intermediate language compilers for compiling functions and scripts.
The MATLAB® Engine is the core of the MATLAB product. It compiles, executes, and interprets MATLAB scripts and programs, as well as runs the M-files and M-links created by the MMC. It also allows the exchange of data between MATLAB applications, the MathWorks M-files and M-links, and other programming languages, including C, C++, and Visual Basic. 827ec27edc