The matrix analysis functions det, rcond, hess, and expm also show significant increase in speed on large double-precision arrays. 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.
Alternatively, you can calculate the dot product A B with the syntax dot (A,B). The operation is not memory-bound processing time is not dominated by memory access time. The result is a 1-by-1 scalar, also called the dot product or inner product of the vectors A and B. 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. The function performs operations that easily partition into sections that execute concurrently.
