Based GPU approach to accelerate spectroscopy Raman spectrum processing

Abstract

Raman spectrometry is a technique that allows detecting chemical products through a number of representative peaks found in an image spectrum or numeric series of data. The Raman spectrum machine generates a CSV file or an image as a curve which is the result of the diagnosis product. The analysis of the spectrum peaks permits to detect the chemical origin of the concerned product. Scientists do this operation manually, which makes it hard and long in terms of time. Graphics Processing Units (GPUs) allow us to make the processing faster and more efficient, thanks to its multicore architecture. The aim of the present paper is to propose a new GPU based approach to automate the molecule detection operation using image-processing techniques with OpenCL parallel implementation. We propose two parallel solutions, which will be compared to each other. We apply the exploited approach to analyze ionic liquids and biomaterials samples.