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How MATLAB makes the distinction between P-Cores and E-Cores?

  It is known that modern CPUs have both Performance cores (P-cores) and efficiency cores (E-cores), different types of CPU cores that have different purposes and are designed for different tasks. P-cores typically have higher clock speeds and designed for high-performance tasks, while E-cores operate at lower clock speeds and focus on energy-efficient processing. In MATLAB, maxNumCompThreads returns the current maximum number of computational threads. Currently, the maximum number of computational threads is equal to the number of physical cores on your machine. How MATLAB makes the distinction between P-Cores and E-Cores ? NOTE:- Matlabsolutions.com  provide latest  MatLab Homework Help, MatLab Assignment Help  ,  Finance Assignment Help  for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects...
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Matlab mldivide returns NaN when there are multiple solutions

 I have two matrices:

 

A = [ -1 0  0;
       1 1 -1;
       0 -1 1 ];
B = [-1; 0; 1];

and I want to solve the following equation:

Ax=B

when I use mldivide function I get a matrix of NaNs

 

X = mldivide(A,B)
X =

   NaN
   NaN
   NaN

Knowing there are multiple solutions to this problem I manually tested if one of them, namely [1;0;1] returns B:

 

A*[1; 0; 1]

and, as expected, I reassured myself that it is one of multiple solutions. So here is my question: why does mldivide return incorret solution?


NOTE:-


Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help , Finance Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.


Your matrix A is singular. The MATLAB doc states that in these cases, mldivide is unreliable ("... When working with ill-conditioned matrices, an unreliable solution can result ...") and suggests to use lsqminnorm( ) or pinv( ) instead (see "Tips"). E.g.,

 

>> A = [ -1 0  0;
    1 1 -1;
    0 -1 1 ];
>> B = [-1; 0; 1];
>> A\B
Warning: Matrix is singular to working precision. 
 
ans =
   NaN
   NaN
   NaN
>> A*ans-B
ans =
   NaN
   NaN
   NaN

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