Accelerating Data-Intensive Applications: A Cloud Computing Approach to Parallel Image Pattern Recognition Tasks
Performance is an open issue in data intensive applications, such as image pattern recognition tasks. To process large-scale datasets with high performance more resources and reliable infrastructures are required for spreading the data and running the applications across multiple machines in parallel. The current use of parallelism in high performance computing and with multi-core hardware support is costly and time consuming. To remove the burden of building, operating and maintaining expensive physical resources and infrastructures, Cloud computing is emerging as a cost-effective solution to address the increased demand for distributed data, computing resources and services.