The matrix analysis functions det, rcond, hess, and expm also show significant increase in speed on large double-precision arrays. 67 Mathematica / Wolfram Language 68 MATLAB / Octave 69 Maxima. The matrix multiply (X*Y) and matrix power (X^p) operators show significant increase in speed on large double-precision arrays (on order of 10,000 elements). As a general rule, complicated functions speed up more than simple functions. R ( ) ( cos sin sin cos ) cos ( 1 0 0 1) + sin ( 0 1 1 0). as you'd expect, and this might be regarded as a kind of proof of Euler's identity. The operation is not memory-bound processing time is not dominated by memory access time. You can then use matrix exponential to verify that. For example, most functions speed up only when the array contains several thousand elements or more. The data size is large enough so that any advantages of concurrent execution outweigh the time required to partition the data and manage separate execution threads. They should require few sequential operations. These sections must be able to execute with little communication between processes. can calculate all the fluxes and Jacobians say by using Maple or Mathematica. to Det m - id x where id is the identity matrix of appropriate size. The function performs operations that easily partition into sections that execute concurrently. I n M) with In I n the identity matrix of size n n (and det the matrix. 2x2 Matrix Multiplication Calculator is an online tool programmed to perform.

Mathematica identity matrix