Convert Component Based Serial Code to Parallel to an Automatic Framework

Abstract

— With the increase of modular software development to reduce the delivery time, the increase of parallel processing is also increasing. The serial software codes, in the form of component or without the components, cannot leverage the performance of the modern hardware capabilities. Hence majority of the recent software developments are happening considering the parallel processing of the source code. The parallel processing of the source code is not only the responsibility of hardware or GPUs, rather the source codes are also to be written in specific form to take the benefits of parallel processors. Subsequently, not constrained to the improvement in the calculation structure, the utilization of parallel execution of the projects is likewise to be considered. GPUs are ordinarily utilized handling units to accelerate the application execution in diversion improvement. The GPUs can be used to parallelize the application execution to achieve the clock used to the most extreme. The real test is to plan or re-structure the application code from customary sequential programming dialects to the parallel codes, which can take the benefits of GPU centres. Nevertheless, developing the parallel software code components demand a higher development skill from the developer’s community, which is difficult to obtain. Also, apart from the newer applications, there are many legacy software components which are also under the demand for conversion in the parallel form. A good number of parallel research attempts are carried out to convert the serial code into a parallel form code, nonetheless, the attempts were manual and needs a very high amount of programming and the application APIs knowledge. Hence, this research attempts to build a framework to automatically convert the serial source code components into parallel source code components to be plugged in to the parallel applications without misplacing the benefits of component-based and the benefits from parallel processing of software codes. The proposed novel framework demonstrates a nearly 97% reduction of code execution time.