1/30/2024 0 Comments Scilab vs octave![]() The feval functions is not parallelism but a way to vectorize a conventional function.Scilab matrix arithmetic and parallel_run are vectorized or parallel depending to the platform, hardware and version of the Scilab. OpenMP interface for multithreading/task-parallelism. OpenCL interfaces for GPU/data-parallel computation. There is MPI interface for distributed computation (multithreading/parallelism on multiple computers). Given the above description there are lot in the FOSS world for each one of these. Basically like a mom cooking and cleaning and taking care of its kid at the same time but doing only one job at the time :) Anyone who needs MATLAB specifically isn't going to use it because it is lagging behind and lacks the toolboxes, and anyone who doesn't need MATLAB specifically is going to use something else because it gives them more freedom and flexibility. Concurrent or asynchronous is when you have just one computational unit, but it does multiple jobs at the same time, without blocking the processor unconditionally. So it is hard to get people excited about contributing to Octave. ![]() There is also task parallelism which mostly refers to ruing a task on multiple threads, each processed by a separate CPU core. Parallel computation, mostly used for GPU computing (data paralleism), is when you run massive amount of arithmetic on big arrays, using GPU computational units. It is the way you write the code not necesarily how it is being handled by the computer. For example map function and list comprehension on Python is vectorised computation. Without going much into the details vectorized programing is a way to avoid ugly for-loops. Something you should consider is the difference between vectorized, parallel, concurrent, asynchronous and multithreaded computing. Specifically for SIMULINK alternatives see this post. To see a list of Free and Open Source alternatives to MATLAB-SIMULINK please check its Alternativeto page or my answer here.
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