  Quantum multi-programming is a method utilizing contemporary noisy
intermediate-scale quantum computers by executing multiple quantum circuits
concurrently. Despite early research on it, the research remains on quantum
gates or small-size quantum algorithms without correlation. In this paper, we
propose a quantum multi-programming (QMP) algorithm for Grover's search. Our
algorithm decomposes Grover's algorithm by the partial diffusion operator and
executes the decomposed circuits in parallel by QMP. We proved that this new
algorithm increases the rotation angle of the Grover operator which, as a
result, increases the success probability. The new algorithm is implemented on
IBM quantum computers and compared with the canonical Grover's algorithm and
other variations of Grover's algorithms. The empirical tests validate that our
new algorithm outperforms other variations of Grover's algorithms as well as
the canonical Grover's algorithm.
