Biometrics matching has been widely adopted as a secure way for identification and verification purpose. However, the computation demand associated with running this algorithm on a big data set poses great challenge on the underlying hardware platform. Even though modern processors are equipped with more cores and memory capacity, the software algorithm still requires careful design in order to utilize the hardware resource effectively. This research addresses this issue by investigating the biometric application on many-core platforms. Biometrics algorithm, specifically Daugman's iris matching algorithm, is used to benchmark and compare the performance of several manycore platforms. The results show the ability of the iris matching application to efficiently scale and fully exploit the capabilities offered by many-core platforms and provide insights in how to migrate the biometrics computation onto high-performance many-core architectures.