Two measures of the efficiency of an algorithm are the number of floating point operations (flops) performed and the elapsed time.
The MATLAB function flops keeps a running total of the flops performed. The command
flops(O)
will reset flops to 0. Hence, entering
flops(O)
immediately before executing an algorithm and
flops
immediately after gives the flop count for the algorithm.
The MATLAB function clock gives the current time accurate to a hundreth of a second (see help clock for more information). For example, given two such times tl and t2, the command
etime(t2,tl)
gives the elapsed time from tl to t2. One can also, for example, measure the time required to solve a given linear system A = b, using Gaussian elimination as follows:
time = clock; x = A\b; time = etime(clock,time)
You may wish to compare this time--and flop count--with that for solving the system using this command:
x = inv(A)*b;
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