The browser version you are using is not recommended for this site. Please consider upgrading to the latest version of your browser by clicking one of the following links. The number of wireless devices is set to explode and a diverse set of connectivity types will be needed for a significantly larger amount of diverse applications.

Learn more. Artificial Intelligence AI is seeing an explosion of growth and applications. The flood of data that is generated and collected every day and the computations required to allow smarter algorithms to sift through that data more cost effectively drive AI development. As workloads and traffic pattern shift in the data center, Intel FPGAs can anticipate needs and bring optimized hardware acceleration to bear on the critical points.

Intel FPGAs, SoCs, intellectual property IP cores, development platforms, and a software-centric design flow provide a rapid development path with the flexibility to adapt to evolving challenges and solutions in each part of the video or vision pipeline for a wide range of video and intelligent vision applications.

Our solutions enable anyone to develop any application, scaling from single prototype units to hundreds of thousands of units in production. Intel FPGAs provide a variety of security capabilities to secure your reconfigurable logic designs, system, and data. These capabilities include secure fuse-based and battery-backed root keys, encrypted design bitstream, and other key protection, data erasure, and glitch-protection features.

Contact us. Learn how these powerful devices can be customized to accelerate key workloads and enable design engineers to adapt to emerging standards or changing requirements. View all devices. Safari Chrome IE Firefox. Artificial Intelligence Artificial Intelligence AI is seeing an explosion of growth and applications. Data Center As workloads and traffic pattern shift in the data center, Intel FPGAs can anticipate needs and bring optimized hardware acceleration to bear on the critical points.

Intelligent Vision and Video Intel FPGAs, SoCs, intellectual property IP cores, development platforms, and a software-centric design flow provide a rapid development path with the flexibility to adapt to evolving challenges and solutions in each part of the video or vision pipeline for a wide range of video and intelligent vision applications.

Security Intel FPGAs provide a variety of security capabilities to secure your reconfigurable logic designs, system, and data. Need help with your FPGA design? Collaborate with Intel on your next project. You may compare a maximum of four products at a time. Please remove one or more items before adding more. The item selected cannot be compared to the items already added to compare. Please select a comparable product or clear existing items before adding this product.Our website uses cookies including profiling cookies of authorised third parties to give you a better browsing experience, and by continuing to use our site you accept our cookies policy.

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FPGA Applications

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FPGA Common Applications

Solving Key Market Issues. Automotive High reliability for ensuring zero-defects Best-in-class security for secured data and connectivity Supply assurance from credible supplier with high-reliability experience Low power for optimal power efficiency Lowest cost of ownership.

Industrial Increased networking of factory automation M2M—growth of additional sensors and nodes Rise of cloud services requiring decentralized, secure computing Portability becoming more prevalent Cyber security threats and functional safety requirements.The modern world revolves around technology and its evolution. Semiconductor chips and devices play a big role in the development of various technological devices and are some of the most important components of any tech tool applied in any given field or department.

There are various kinds of semiconductor chips and devices and some are preferred over others in particular conditions, applications, and scenarios. One of the most innovative semiconductor product is the FPGA.

Machine Learning For Embedded Applications on FPGAs - Nick Fraser, Xilinx

They are composed of an integrated network or sets of logic blocks placed on a chip; where the circuits are the programmable logic gates. FPGAs consist of individual configurable logic blocks, or CLBs, which are connected through programmable interconnects. As suggested by the name of the semiconductor technology, FPGAs are known for their ability to be programmed when implemented in the field as opposed to other kinds of semiconductor chips e.

As such, it will only perform that one function and cannot be modified to anything else, neither can it be erased and rewritten so as to reuse the chip.

A new one must be created for a new purpose. An FPGA, on the other hand, can be reprogrammed and reused, and is much more flexible when it comes to customization and personalization, especially when deployed out in the field. With the help of an FPGA chip, you can write a program which is loaded onto a silicon chip, and then execute the functions.

If you want to optimize a chip, to fit a certain workload, then you can use an FPGA chip. Like mentioned before, FPGAs are field programmable and offer much more scalability and flexibility. They are able to keep up with modern requirements of high complexity and high performing devices. They also offer greater logic density, embedded processors, DSP blocks, and clocking among other prominent features.

They are, however, cheaper alternatives to ASICs. FPGA are also ideal for systems where consistent updates are a requirement. If a processor needs some changing, then FPGA chips can be used for making those changes if they are installed, eliminating the need to purchase new hardware. If FPGA chips are used in cars, then they can be updated with the help of these chips, even after they have been sold.

These chips are also used frequently by enterprise businesses, because they can be reprogrammed using a data path that matches data analytics, image inference, and even compression. The benefit of using an FPGA for this purpose is that it can be reprogrammed again and again, until a design is finalized and there are no bugs found in the design. Intel, a huge name in the IT industry, uses FPGAs to prototype new permanent chips so as to ensure their quality, function, and integrity.Electronic companies design the hardware dedicated to their products with their standards and protocols which makes it challenging for the end users to reconfigure the hardware as per their needs.

This requirement for hardware led to the growth of a new segment of customer-configurable field programmable integrated circuits called FPGAs. It is a type of device that is widely used in electronic circuits.

FPGAs are semiconductor devices which contain programmable logic blocks and interconnection circuits.

Make your first FPGA application

It can be programmed or reprogrammed to the required functionality after manufacturing. When a circuit board is manufactured and if it contains an FPGA as a part of it. This is programmed during the manufacturing process and further can be reprogrammed later to create an update or make necessary changes.

In microcontrollers, the chip is designed for a customer and they have to write the software and compile it to hex file to load onto the microcontroller. This software can be easily replaced as it is stored in flash memory. In FPGAs, there is no processor to run the software and we are the one designing the circuit.

fpga applications

Hence, they must be configured every time power is supplied. FPGAs are prefabricated silicon chips that can be programmed electrically to implement digital designs. The programmable logic block provides basic computation and storage elements used in digital systems. A basic logic element consists of programmable combinational logic, a flip-flop, and some fast carry logic to reduce area and delay cost.

Modern FPGAs contain a heterogeneous mixture of different blocks like dedicated memory blocks, multiplexers. Configuration memory is used throughout the logic blocks to control the specific function of each element. It consists of multiplexers pass transistors and tri-state buffers.

Pass transistors and multiplexers are used in a logic cluster to connect the logic elements. With advancement, the basic FPGA Architecture has developed through the addition of more specialized programmable function blocks.

FPGA Architecture design comprises of design entry, design synthesis, design implementation, device programming and design verification. Design verification includes functional verification and timing verification that takes place at the time of design flow.

The following flow shows the design process of the FPGA. The design entry is done in different techniques like schematic based, hardware description language HDL and a combination of both etc.

If the designer wants to deal with hardware, then the schematic entry is a good choice. If the designer thinks the design in an algorithmic way, then the HDL is the better choice.Xilinx serves the aerospace and defense industry with commercial, defense, and space grade system-level solutions that span industry-leading FPGA and SoC devices, advanced IP solutions, and the next generation of design tools.

Our heritage has led to a deep understanding of our customers and the requirements to successfully implement and deploy the next generation of ground-based, airborne, and space-based applications.

fpga applications

Continuous focus on this market enables Xilinx to reduce mission risk and system cost with our industry-leading solutions. Heritage in specialized defense-grade silicon products makes Xilinx the smart choice to meet the rigorous demands of rugged environments and military systems.

Defense-grade devices include, amongst other things, extended temperature range and fully leaded Pb components in ruggedized packaging. The Xilinx Bare Die program satisfies the need for further SWaP-C requirements beyond small form factor packaging for systems that must have the lowest possible size and weight.

Xilinx provides most products families in bare die and in some cases, whole wafer form. Experienced packaging partners are available to help customers with assembling and processing Bare Die if needed. These assemblies are typically modules based on organic or silicon substrates. Please note that Bare Die products are sold under special terms and conditions. Also, special documentation is available to allow customers to design with and assemble Bare Die.

See the Bare Die page for more information. See the avionics site for more details or contact avionics xililnx. Xilinx will be increasing number of advanced design flow features over the next year and into the future. This suite offers current support for the latest advanced design flows which facilitate safe, secure, high performance, and low power solutions. Xilinx enables advanced DSP capabilities through hardware, intellectual property cores, and tool flows.

This solution allows for fully independent software and hardware development efforts. The SoC device additionally accommodates hardware acceleration and expansion capabilities with custom IP and peripherals embedded into the FPGA fabric that are tightly integrated to and called from the processor subsystem.

Learn more about the Zynq Family. The highly flexible architecture, plus a rich instruction set optimized for embedded applications, delivers the exact processing system you need at the lowest system cost possible. Learn more about the MicroBlaze processor. This processor maintains the flexibility and configurability of the commercial version yet is delivered with full lifecycle artifacts from PHAC to HAS, and everything in betweenintegration guidance, and certification support.

See avionics site and developers site and email avionics xilinx. Xilinx realizes the integral importance of IP solutions. For DO IP support, see the avionics site. Aerospace and Defense customers rely on quality components to enable long lasting mission critical systems. Xilinx is the first company to yield and deliver reliable 28nm devices built on the HPL process. This is no accident, it with much diligence, analysis, and attention to design and fab process that we are able to deliver such results.

Xilinx is dedicated to delivering quality products and we have been well recognized within industry for doing just that. We are one of few semiconductor companies to publish annual quality report and other failure rate data. See our quality page for more detail. Xilinx offers industry leading expertise and extensive experience in SEU effects with more than a decade of heritage in the area of radiation effects testing and mitigation. And see our dedicated site for background on our general SEU work and heritage.

Xilinx is an industry leader, with extensive heritage, in delivering secure solutions encompassing anti-tamper and fault tolerance. Visit the Secure Solutions page to learn more. These systems now combine high-resolution multispectral sensors with traditional visible and thermal sensors as well as positioning or geolocation data to drive displays or autonomous decision making in real time.

Xilinx - Adaptable. Applications Aerospace and Defense. Aerospace and Defense.It is a digital programable chip that is used in electronic products and offers re-programmability capability.

fpga applications

This semiconductor chip is based on programmable interconnection circuits and programmable logic blocks which can be modified to suit the needs of the user. With thousands of logic blocks placed on a single chip and each capable of executing logic functions, FPGAs are able to complete implementations at high speeds and with incredible efficiency. One advantage is the parallel nature of the FPGAs that allows them to offer higher processing power and speeds and this they give better response times and an overall improved performance as compared to other modern microprocessors.

The dataflow and processing speed are also rather limited in microprocessors, a factor which is much better and improved in FPGAs. The second advantage is cost. This makes them the perfect for low volume and mid-volume size production runs. The re-programmability of FPGAs is a big advantage, so that it can be used for prototyping purposes and and designs can be tested out or verified through these FPGAs before they are fabricated in the form of ASICs, for example.

The flexibility of FPGAs stems from the fact that these semiconductor chips are reprogrammable and reusable, which means that even if you were to make a mistake in the programming, you can modify it or you can use these steps to create prototypes which can then be converted into permanent ASICs. Microcontrollers hardware are fixed and permanent, meaning in order to modify them, we need to make changes in the hardware.

With FPGAs on the other hand, these changes can be made simply by reprogramming the chip to reconfigure the logic cells in FPGAs and their interconnections The parallel execution of FPGAs also adds a layer of trusted reliability to the system. Unlike ASICs, FPGAs do not need to be upgraded or maintained in the same way as they are reprogrammable and can be upgraded or enhanced without a great deal of time and resource investment that would be required to reconfigure permanent circuit boards and hardware.

Since FPGAs work in a parallel fashion, they boast much higher speeds and thus can be used to solve complex computable problems, together with the re-programmability ability — this makes FPGAs both powerful and flexible machines. Some of the most common uses and applications for FPGAs today are:. FPGAs can be divided or classified into three basic types based on their applications as described above:. Low end FPGAs are ideal for systems that demand low power consumption, logic density, and complexity on the chip.

Mid range FPGAs are a marriage between performance and price and are considered to be the ideal solution in most cases as it balances out the density, complexity, and consumption per chip with the cost without compromising too much on either of the factors. While high end FPGAs may be expensive and comparatively consume more power, they also offer the best functionality with the highest logic density and complexity, and the best overall performance. At the end of the day, FPGA offers customizable and powerful computing solutions at a relatively lower cost and leaving behind less of a carbon footprint as compared to some of the other technology in its bracket that is no longer able to provide optimum solutions to modern computing problems.In the 34 years that have passed, FPGAs have been wildly successful and are certainly among the most important electronic devices ever conceived.

FPGAs do one thing exceptionally well: Flexibility. FPGAs can often do what no other device can, bridging gaps between otherwise-incompatible protocols, reconfiguring themselves on the fly to adapt to changing requirements and circumstances, and acting as stand-ins for ASICs and ASSPs that have not yet been created. If your application needs the flexibility of FPGAs, probably nothing else will work. But all that flexibility comes at a cost — price, power, and performance.

Best estimates are that all three of those factors are worse than optimized, dedicated silicon by about a factor of ten. That means that, if you design your application with an FPGA in it, and your application is successful, over time, once your requirements stop changing and your design and architecture get nailed down, replacing that FPGA with something cheaper, faster, and more power-efficient will be high on your list of priorities.

For many applications, that day never comes. By the time there is impetus to remove the FPGA, new requirements have come along that start the clock over again. A new design requires a new FPGA and goes through its own maturation process. So, FPGAs have had many application areas where they remain for decades, even though they are never ever the optimal design solution. This is a problem for FPGA companies, as it limits their growth potential. Instead, FPGA vendors are constantly battling to win new sockets and to re-win old ones.

The requirements are tricky. Training typically happens once, and big-iron servers are used — often with GPUs doing the heavy lifting. Training requires massive floating-point computation, and GPUs are the best fit so far for delivering the required floating-point performance. Inferencing has different requirements than training. Where training is generally done in a data center, inferencing is often done in embedded applications. Most importantly, unlike training, inferencing can be done with narrow bit-width fixed point computation.

Helloooooo FPGAs! Your killer app may have just arrived.


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