The types of functional VLSI chips needed for general and special purpose (computationally intensive) applications are wide ranging, Hence, to reduce the turn-around time of these VLSI chips, mask/field programmable PLAs, gate arrays SLAs and FPGAs are available. However these VLSI arrays are unsuitable for designing ultrahigh performance special purpose VLSI chips. There is a strong need for developing a suitable mask programmable VLSI structures exclusively for designing ultrahigh performance and cost-effective special purpose systems. For this purpose, a macro cell based mask programmable Pacube (PA3—Programmable Array of Array Adders) VLSI array is proposed in this paper. These arrays can be mask programmed for building cost-effective super computing VLSI functional units. Another important feature is the architecture of the macro-cell, which is designed in such a way that the functional units corresponding to the G-set equations when mapped on the macro-cell arrays possess identical data flow control. This leads to a highly simplified control design for executing complex computations.

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Abnormal Voltages in electrical distribution system is a threat to power system security and may cause equipment damages. Reconfiguration aids in the proper distribution of load and thus improving the voltage profile. The multi objective framework including node voltage deviation as primary objective and power loss and reliability as secondary objectives is formulated. The novel meta heuristic method based on binary particle swarm optimization (BPSO) is employed to find the optimal radial distribution network configuration for an assortment of objective function. The effect of inertia weight, position and population of swarm is deeply investigated. The proposed method has been verified on IEEE 33 and 69 bus radial distribution systems and found to be effective in minimizing node voltage deviation. The impact of the reconfigured system on voltage deviation, power loss and reliability has been studied extensively. BPSO calculations are found to be simple and has good Convergence characteristics in comparison with other meta heuristic techniques.

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