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Parallel programs previously implemented on complex parallel computers resulted in small number of software developers programming on these computers except for those who understand the application domain and had resources and skill to program on this platform. Most general-purpose computers today having multicore processors and are parallel in architecture. Hence, software developers can cost-effectively take advantage of implementing multicore multithread parallel applications gaining benefits in computing power. This study explores shared memory multicore multithread programming with OpenMP in small scale computers. Laptops with Unix and Linux based platform, Mac OS X and Ubuntu are used to run a popular regular program, matrix multiplication to show the improvement in performance. OpenMP design issues including threading parallelized loop, loop scheduling and partitioning, and sharing and declaring data or memory is emphasized. This can motivate software developers implementing multicore multithread parallel programs in smaller-scale systems and advance to specialized hardware as requirements grow.