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Eight Cutting-Edge Technologies that use FPGA

Posted by Nadeesha Thewarapperuma

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May 11, 2017 10:48:43 AM


1) Ultra-fast financial transactions

The hardware behind these systems are enabled using FPGA. When it comes to automated financial trading, your success depends on the speed and accuracy of a transaction. FPGA are used to build systems which enable low-latency.

Xilinx's 7-series FPGA are used to power these systems. The Virtex-7 families, Kintex-7, and Zynq 7000 SoC are used to build financial trading platforms.


2) Machine learning

Image search engines are becoming more sophisticated with each passing day. Search engines are now built using deep neural networks, allowing machines to learn as they go along. Nowadays, image searches are faster and more accurate compared to what had been there ten years ago.

Xilinx's Virtex Ultrascale+ FPGA are used to enable the sophistication required by a heavy-duty machine learning platform.


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3) Artificial Intelligence

The task of building a true, sentient being is not easy, but a lot of companies are taking up the challenge. Right now, companies are building robots that are specialized to handle a single type of task. By focusing on one special task, the robot can be built to handle all dynamics around that task, things ranging from different scenarios to learning opportunities.


4) Internal Applications

This goes along with the financial trading platform. Often, companies need software and hardware that is custom-built to meet the company's needs. These specialized systems are built to meet the needs of the company, depending on the budget on hand and the performance level that is required.


5) Healthcare Products

Healthcare will be one of the fastest growing markets in the world. Machines will be used along with healthcare services. Advanced healthcare machines are now built to provide diagnoses, saving patients the time and money of obtaining a second opinion.

Read our recent blog on FPGA use in 2017.


6) Autonomous Vehicles

The hardware behind ADAS systems will also require a high-end FPGA, preferably one that can handle and process large amounts of data in a matter of seconds and then make an accurate decision based on input from the outside world. An ADAS system will also be enabled with deep neural networks, allowing the system to learn from experience.

This is one of the reasons why companies like BMW, Google, Uber and Tesla are relying on hours and hours of prototype driving. As the ADAS system learns, it will know how to react to certain situations.


7) Drone advancement

There's talk that drones should operate so that it's like a flock of birds. Right now, lone drones are sent on high-profile missions, but a single drone is easier to target and eliminate. When there are multiple drones around, it is much easier to complete a mission.


8) Wireless networking

5G systems are already in test phase and will be introduced by the year 2020. 5G systems will be used to enable communication between IoT devices, ensuring speed, accuracy and low-latency.


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Topics: FPGA, Autonomous Driving, ADAS, machine learning

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