Designing Parallel Operation for High-Performance Cloud Computing Using Partition Algorithm

Cloud computing comes up with the efficiency of storing an enormous amount of data to retrieve and to maintain. It has a huge amount of advantages for platforms such as Amazon, Google, and Microsoft. Some best advantages are maintaining quality, cost reduction, preventing the loss, extendibility. With all these, the performance of cloud computing assumes a significant job in every stage of the cloud. The expectation of platform viewers and owners need the performance of the cloud should be skyscraping. But achieving the high performance of cloud computing is a big deal in reality. The performance of cloud computing can analyze based on the environment which is used. The high-performance cloud computing (HPCC) is defined as a sort of distributed computing arrangement that fuses principles, systems, and components from distributed computing. The total arrangement may incorporate capacity, equipment, and application programming, which will all be conveyed through the cloud on an on interest premise. So, in this paper, we had briefly explained cloud models and services. The main discussion that is carried out here is the difference between CC and HPCC. The partition algorithm is used for designing parallel operation for HPCC to lift in selection at the expense of supply and to reduce the performance time of taking input operations (or) conditions.