Biometric Matching System’s FPGA Tech Offers Cost and Environmental Savings: Thales

Biometric Matching System's FPGA Tech Offers Cost and Environmental Savings: Thales

Thales is highlighting the efficiency of some of the infrastructural technology supporting its Biometric Matching System, announcing that it’s using commercial Field-Programmable Gate Array technology developed in the aerospace industry to support the backend processing of its government-focused biometric identification systems.

As Thales explains, the FPGA technology was originally designed to support ultra-low latency computing in the fields of finance and scientific industry. Thales’ subsidiary, Gemalto, has leveraged the technology to support its BMS platform, which can require the processing of hundreds of millions of biometric database records in just a couple of seconds, thanks in large part to its growing use in border management applications.

To that end, FPGA tech “also allows for much faster data processing and greater matching accuracy, while at the same time limiting infrastructure costs and cutting carbon emissions,” Thales said in a statement.

While keeping costs down is a tenet across the business world, Thales’ emphasis on minimizing carbon emissions is a timely one in the same week that the International Monetary Fund downgraded its economic forecasts for 2020-2021 in a report that said climate change “already endangers health and economic outcomes” around the world. The International Panel on Climate Change has said that limiting global temperature rise to 1.5 degrees Celsius will require “rapid, far-reaching and unprecedented changes in all aspects of society,” while current emissions trends are on track to drive the temperature well above two degrees, an outcome that the IPCC has described as “catastrophic”.

For its part, Thales’ SVP of Identity & Biometric Solutions, Youzec Kurp, said that the FPGA-based system “can cut data centre investment and space overall by more than a half, whilst reducing CO2 emissions by around 50%” compared to an alternative method based on a Central Processing Unit.

January 21, 2020 – by Alex Perala