When using a tool such as Windows Task Manager, MATLAB may appear to use only half of the CPU cores available on the computer, when in fact the "unused" half is actually the virtual cores created by hyper-threading. Simultaneous multithreading gives the appearance that a computer has twice as many cores than it actually has. MATLAB (2014a) or higher on all platforms supported by MATLAB, including Windows, MacOS X, Unix and Linux. Virtual cores may modestly improve overall system performance, but they are likely to have little effect on the performance of MATLAB applications.
However, on some processors, a single FPU may be shared between multiple CPU cores, potentially creating a performance bottleneck. On many CPUs, the number of Floating-Point Units (FPUs) equals the number of CPU cores. MATLAB performance is dependent on the presence of floating-point hardware. Support for Windows 7 will be discontinued in an upcoming release. MATLAB R2016a is here, the world's most powerful numerical computing environment, design and graphical simulation for dynamic and embedded systems.
#Matlab 2014a system requirements serial#
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#Matlab 2014a system requirements update#
For additional capability, Parallel Computing Toolbox offers parallel programming constructs that more directly leverage multiple computer cores. On Windows 11, MATLAB R2021b update 1 is required. System Requirements - Supported platforms for the OM1106 User Interface.
But not all MATLAB functions are multithreaded, and the speed-up varies with the algorithm. MATLAB automatically uses multithreading to exploit the natural parallelism found in many MATLAB applications. Computers with more CPU cores can outperform those with a lower core count, but results will vary with the MATLAB application.
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