All modern personal computers including desktops, notebooks, smartphones, and tablets, are examples of general-purpose computers. General-purpose computing incorporates ‘Von Neumann’ approach, which states that an instruction fetch and a data operation cannot occur simultaneously. Therefore, being sequential machines, their performance is also limited.
On the other hand, we have the Application Specific Integrated Circuits (ASICs) which are customized for a particular task like a digital voice recorder or a high-efficiency Bitcoin miner. An ASIC uses a spatial approach to implement only one application and provides maximum performance. However, it can’t be used for tasks other than those for which it has been originally designed. FPGAs act as a middle ground between these two architectural paradigms.
Field Programmable Gate Array (FPGA) is a semiconductor IC where a large majority of the electrical functionality inside the device can be changed during the PCB assembly process or even changed after the equipment has been shipped to customers out in the ‘field’.
FPGA enables you to program product features and functions, adapt to new standards, and reconfigure hardware for specific applications even after the product has been installed in the field — hence the term field programmable. The array of gates that make up an FPGA can be programmed to run a specific algorithm, using the combination of logic gates (usually implemented as lookup tables), arithmetic units, digital signal processors (DSPs) to do multiplication, static RAM for temporarily storing the results of that computation and switching blocks that let you control the connections between the programmable blocks. FPGA functionality can change upon every power-up of the device. So, when a design engineer wants to make a change, they can simply download a new configuration file into the device and try out the change.
The combination means that FPGAs can offer massive parallelism targeted only for a specific algorithm, and at much lower power compared to a GPU. This often makes them first choice for the development of new devices or systems. These programmable logic devices have long been used in telecom gear, industrial systems, automotive, and military and aerospace applications.
They are reprogrammable and have low NRE costs when compared to an ASIC. FPGAs reduce risk, allowing prototype systems to ship to customers for field trials, while still providing the ability to make changes quickly before ramping to volume production. However, FPGAs are less energy efficient when compared to ASICs and also not suitable for large volume productions.
FPGAs can directly be connected to inputs and can offer very high bandwidth and low latency. Low latency is what you need if you are programming the autopilot of a jet fighter or a high-frequency algorithmic trading engine: the time between an input and its response as short as possible.
This is where FPGAs are much better than CPUs (or GPUs, which have to communicate via the CPU). With an FPGA it is feasible to get a latency around or below 1 microsecond, whereas with a CPU a latency smaller than 50 microseconds is already very good. Moreover, the latency of an FPGA is much more deterministic. One of the main reasons for this low latency is that FPGAs can be much more specialized: they do not depend on the generic operating system, and communication does not have to go via generic buses (such as USB or PCIe). While FPGAs used to be selected for lower speed/complexity/volume designs in the past, today’s FPGAs easily push the 500 MHz performance barrier.
Modern FPGAs with large gate arrays, memory blocks, and fast IO are suitable for a wide range of tasks like speech recognition, artificial intelligence, next-generation wireless networks, advanced search engines and high-performance computing. Some FPGAs are essentially systems-on-a-chip (SoC), with CPUs, PCI Express and DMA connections and Ethernet controllers, turning the programmable array into a custom accelerator for the code running on the CPU.
For in-depth understanding on FPGA technology and applications please visit: Mastering FPGA-Based System Design: From Concept to Implementation
Field-programmable gate arrays (FPGAs) are integrated circuits that can be configured to perform a variety of functions. They have been used in a wide range of applications for many years, but their use has accelerated in recent years as they have become more powerful and affordable.
One of the biggest trends in FPGAs is the increasing use of high-level synthesis (HLS). HLS allows developers to use high-level languages, such as C and C++, to create FPGA designs. This makes it much easier to develop FPGA designs, as developers do not need to learn a new hardware description language (HDL).
Another trend in FPGAs is the increasing use of hard cores. Hard cores are pre-designed blocks of logic that can be used to implement specific functions, such as a processor or a communications controller. This can save time and money, as developers do not need to design these functions from scratch.
FPGAs are also becoming increasingly popular for artificial intelligence (AI) applications. This is because FPGAs can be used to accelerate AI algorithms, such as deep learning. FPGAs are well-suited for AI applications because they can be programmed to perform specific operations very quickly.
FPGAs are being used in data centers to accelerate data processing and improve energy efficiency. For example, FPGAs can be used to implement custom algorithms for machine learning, data compression, and networking.
Data center customers increasingly use hardware accelerators, like FPGAs, when more computational speed is required from server systems running networking and cloud-based applications such as artificial intelligence training/inferencing or database-related workloads. The effective performance of hardware accelerators depends heavily on the communications bandwidth and latency between one or more server CPUs, available system memory and any attached accelerator (GPU, FPGA, application-specific standard products, etc.).
The silicon photonics platform provides low cost, low energy and small optical interconnects resulting in integration between computational components and optical interconnects. Developers are further investigating FPGA-enabled silicon photonic interconnects for computational and processor-to-memory interconnects on work with Oracle Certified Master (OCM) architectures. FPGA-based optical network interface can execute primitives compatible with OCM data transactions.
Photonic Networks for Hardware Accelerators: Hardware Accelerators normally needs high bandwidth, low latency, and energy efficient. The high performance computing systems has critical performance is shifted from the microprocessors to the communications infrastructure. By uniquely exploiting the parallelism and capacity of wavelength division multiplexing (WDM), optical interconnects that able to address the bandwidth scalability challenges of future computing systems. The multi-casted network that uniquely exploits the parallelism of WDM to serve as an initial validation for architecture. Two FPGA boarded systems emulate the CPU and hardware accelerator nodes. Here FPGA transceivers implement and follows a phase-encoder h eader network protocol. The output of each port is individually controlled using a bitwise XNOR of port’s control signal. Optical packets are send through the network and execute switch and multicasting of two receive nodes with most reduced error.
FPGA chips to accelerate AI
FPGAs are field-programmable gate arrays that can be configured to perform a variety of functions. They are increasingly being used to accelerate AI applications, such as machine learning and deep learning.
One of the main advantages of FPGAs for AI is their high performance. FPGAs can perform complex calculations very quickly, which is essential for AI algorithms that need to process large amounts of data in real time.
Another advantage of FPGAs is their flexibility. FPGAs can be configured to perform a variety of functions, which makes them well-suited for AI applications that need to be customized for specific tasks.
Finally, FPGAs are relatively power-efficient, which is important for AI applications that need to run on battery power.
Technology innovations in today’s FPGAs enable improvements in many common AI requirements:
Overcoming I/O bottlenecks. FPGAs are often used where data must traverse many different networks at low latency. They’re incredibly useful at eliminating memory buffering and overcoming I/O bottlenecks — one of the most limiting factors in AI system performance. By accelerating data ingestion, FPGAs can speed the entire AI workflow.
Providing acceleration for high performance computing (HPC) clusters. FPGAs can help facilitate the convergence of AI and HPC by serving as programmable accelerators for inference.
Integrating AI into workloads. Using FPGAs, designers can add AI capabilities, like deep packet inspection or financial fraud detection, to existing workloads.
Enabling sensor fusion. FPGAs excel when handling data input from multiple sensors, such as cameras, LIDAR, and audio sensors. This ability can be extremely valuable when designing autonomous vehicles, robotics, and industrial equipment.
Adding extra capabilities beyond AI. FPGAs make it possible to add security, I/O, networking, or pre-/post-processing capabilities without requiring an extra chip, and other data-and compute-intensive applications.
Here are some examples of how FPGAs are being used to accelerate AI:
- Self-driving cars: FPGAs are being used in self-driving cars to process data from sensors, such as cameras and radar, and to make decisions about how to control the car.
- Medical imaging: FPGAs are being used to accelerate the processing of medical images, such as MRI scans and X-rays. This can help doctors to diagnose diseases more quickly and accurately.
- Financial trading: FPGAs are being used to accelerate the processing of financial data, such as stock prices and market data. This can help traders to make decisions more quickly and profitably.
FPGA chips have proven to be a popular choice for data management services in cloud computing, with major players such as Amazon, Cloudera, Google, Hortonworks, and Microsoft Azure using FPGA computing hardware. Microsoft has been utilizing Altera FPGAs in its servers to power neural networks behind services such as Bing searches, Cortana speech recognition, and natural-language translation. In August, Microsoft announced Project Brainwave, which will make FPGAs available as an Azure service for inferencing.
As AI continues to grow in importance, FPGAs are likely to play an increasingly important role in accelerating AI applications.
FPGA for Military Applications
Field Programmable Gate Arrays (FPGAs) have gained a lot of popularity in the military domain due to their versatility and reconfigurability. FPGAs are being widely used in various military applications such as radars, electronic warfare systems, missiles, and many others.
Advantages of using FPGAs in military applications:
- Reconfigurability: One of the primary advantages of FPGAs is their reconfigurability. Military applications often require the ability to modify the system to accommodate new requirements or to adapt to changing environments. FPGAs provide the flexibility to reconfigure the system without requiring significant hardware changes.
- Low Latency: In military applications, low latency is critical, especially in communication and radar systems. FPGAs can process data in real-time with extremely low latency, making them ideal for military applications.
- High Reliability: Military systems need to operate in harsh environments, which can cause electronic components to fail. FPGAs are designed to operate in extreme temperature, vibration, and radiation environments, making them highly reliable.
- Power Efficiency: FPGAs are power-efficient compared to traditional processors, making them ideal for battery-powered military devices.
Field programmable gate arrays (FPGAs) are becoming increasingly important in military applications due to their unique combination of high performance, high capacity, and high level of integration. FPGAs are also highly safe and are equipped with anti-tamper technology, making them a top choice for defense applications. In this article, we’ll explore why FPGAs are so important in military applications and how they are used to improve the efficiency of data center systems, military radars, and electronic warfare systems.
One of the key advantages of FPGAs in military applications is their flexibility. FPGAs can be reprogrammed on the fly, which means that they can be adapted to handle different workloads and tasks as needed. This flexibility allows FPGAs to be used in a wide range of applications, from high-performance computing to image processing and signal processing. Additionally, FPGAs can be used to speed up the data processing required in military applications, which is essential for real-time decision-making.
Another key advantage of FPGAs is their ability to handle heavy workloads with high bandwidth and low power consumption. This makes them ideal for use in portable devices such as smart munitions, radar, and secure radios, where power consumption is a decisive factor. FPGAs can provide high bandwidth radio and image signal processing, anti-tamper, and data security capabilities, all while consuming minimal power.
FPGAs are also used extensively in military radars, which require high-speed signal processing to detect and track incoming threats. FPGAs can be used to implement the digital signal processing (DSP) algorithms required for radar signal processing, enabling radar systems to track targets with a high degree of accuracy. In addition, FPGAs can be used to implement image processing algorithms for optical and infrared sensors, allowing military personnel to identify threats more quickly and accurately.
In electronic warfare systems, FPGAs are used to implement signal processing algorithms that are essential for detecting, identifying, and countering threats. FPGAs are also used in anti-tamper systems, which are designed to protect sensitive information from unauthorized access. FPGAs are highly secure and can be equipped with advanced security features such as encryption and authentication, making them a top choice for electronic warfare applications.
Missile Systems: FPGAs are used in missile systems for guidance and control. FPGAs can be programmed to perform complex control algorithms and handle sensor data in real-time.
Cybersecurity: FPGAs can be used to implement hardware-level security features such as encryption and decryption. Military systems require high-level security to protect against cyber threats, and FPGAs are ideal for implementing secure systems.
In conclusion, FPGAs are becoming increasingly important in military applications due to their flexibility, high performance, and low power consumption. FPGAs can be used to provide high bandwidth radio and image signal processing, anti-tamper, and data security capabilities for smart munitions, radar, and secure radios. By providing soldiers with high-tech capabilities in a compact and portable package, FPGAs are helping to improve the efficiency and effectiveness of military operations.
In Defense FPGA devices are used due to reduced risk, high performance, high capacity, high level of integration, highly safely and ANTI-Tamper technology. FPGA can be used to speed-up the data procession. Defense-graded FPGAs has flexibility shows the endurance of heavy workload. For modern soldier to be successful in the battlefield, it is imperative that they be equipped with gear that delivers high-tech capabilities at the lowest size and weight possible. Mission life is as key as portability, and power consumption is a decisive factor. FPGAs can provide high bandwidth radio and image signal processing, anti-tamper, and data security capabilities for smart munitions, radar, and secure radios.
Today’s secure communications devices are faced with a number of design challenges. Wireline products must meet aggressive demands for data bandwidth to achieve 40-Gbps and 100-Gbps throughput, while often providing a tamper-resistant platform for cryptographic services for applications such as the JIE. Wireless products are developed under strict requirements for reduces size, weight, and power (SWaP) to enable next-generation mobility for military radios that can simultaneously support multiple waveforms such as SRW, WNW, and MUOS. Software defined ratios (SDR) used to re-configurability all transmissions data. FPGA are natural enablers of SDR applications.
Secure communications design challenges apply to wired and wireless systems. Cryptographic functionality is an additional problem that is common to both systems. Information assurance systems with cryptographic capabilities including the Global Information Grid (GIG) support network performance in 40G to 100G and beyond. Net-centricity insures that what the warfighter sees on the ground can be linked to airborne and ground based assets. Strong encryption is key to ensuring communications and data security at ever increasing data throughput rates. Strong cryptographic algorithms implemented on FPGAs that are secure by design provide the foundation for trusted information assurance systems.
Enhanced wireless radios require interoperability and security using commercial, AES, Suite A, and Suite B encryption algorithms. These enhanced radios link firefighters, emergency, medical, and law enforcement systems together while optimizing size, weight, power and cost (SWaP-C). Next generation military-grade trusted communications and SDR platforms must generate compatible waveforms, assuring operational compatibility while at the same time supporting multiple platforms and missions with field update capability. Intel FPGAs enable wireless communications systems to meet these challenges.
Radar has been a foundational technology area in which the semiconductor industry has played a large role for the last two decades. In today’s modern radar systems, Active Electronically Scanned Array (AESA) is the most popular architecture. Going forward, next-generation radar architectures such as digital phased array and synthetic aperture radar (SAR) with ground moving target indicator (GMTI) will be the emerging technology. To achieve this, parameters such as high-performance data processing, ultra-wide bandwidth, high dynamic range, and adaptive systems needed for diverse mission requirements are some of the most common challenges to system designers. An FPGA is an ideal, and in some cases necessary, solution in addressing these challenges. The FPGA are used to transform range-azimuth onto an x-y coordinate plan in radar scan converter systems. There is a need for converting with high speed and accuracy of millions of data points
In electronic warfare, the key drivers for continuous enhancement are Electronic-counter-counter-measures (ECCM). It has the ability to rapidly analyze address multiple threads in the short time frame. The electromagnetic spectrum is used to obstruct opponents and allow allies unhindered access to the EM spectrum. FPGA offers an ideal solution to these performance requirements in critical high-speed processing, to follow different electronic attack (EA) techniques.
In electronic warfare systems, key drivers for continuous enhancements are electronic counter-counter-measures (ECCM), stealth technologies, closely interlinked smart sensor networks, and intelligent guided weapons. These systems must be able to rapidly analyze and respond to multiple threats in very short time frames. In attempting to find target signatures in broadband noise, architects are seeking to perform complex processing such as fast Fourier transforms (FFTs), Cholesky decomposition, and matrix multiplication. Multiple software-generated waveforms are then transmitted to provide false targets, while powerful wideband signals provide overall cover. These shifting tactical responses require agile, high-performance processing. The entire system frequently resides in an airborne platform and must meet strict requirements for heat dissipation along with size, weight, power, and cost (SWaP-C) constraints.
A typical system design, uses a channelizer and inverse-channelizer to process high-bandwidth input signals. The number of channels are flexible so system designers can allocate hardware resources versus system performance as needed. FPGAs offer an ideal solution to these performance requirements in the critical high-speed processing-intensive paths, a typical electronic warfare system with different electronic attack (EA) techniques.
The global FPGA market size is projected to grow from USD 8.0 billion in 2022 to reach USD 15.5
billion by 2027; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 14.2% from
2022 to 2027.
The proliferation of AI and IoT technologies worldwide, rising adoption of FPGAs in ADAS, surging deployment of data centers and high-performance computing (HPC), and mounting demand for FPGA hardware verification in avionics are the factors driving the growth of the market.
The FPGAs market is predicted to expand as the production volume and demand for telecommunications, data centers, and automotive products and solutions such as wireless baseband solutions, radio solutions, wireless modems, network processing cards, and electrical devices grow. FPGAs are increasingly being employed in data centers to offload and speed specialized services. This factor is predicted to propel the FPGA industry forward. ‘
The expansion of the FPGA market is likely to be aided by the significant increase in demand for data centers as a result of the increasing incorporation of IoT in many sectors. FPGA helps data centers boost their processing performance. The growing demand for efficient computing, greater scalability, dependability, and storage, as well as the use of HPC in the cloud, are projected to propel the FPGA market forward.
Furthermore, the FPGA market is expected to grow due to the increased use of FPGAs as an Infrastructure-as-a-Service (IaaS) resource by cloud customers. Several cloud service providers are using field programming gate arrays to speed up network encryption, deep learning, memory caching, webpage ranking, high-frequency trading, and video conversion.
Key factors fueling the growth of this market include the increase in the global adoption of AI and IoT, ease of programming & faster time-to-market of FPGA than ASIC, and incorporation of FPGA in ADAS.
The increasing demand for artificial intelligence and machine learning is likely to boost the FPGA market value. The introduction of nano bridge FPGA is projected to heighten the market growth, owing to technical advancements, such as being high density, which reduces the area occupied by the logic circuit.
Europe is largely focusing on industry 4.0 technology to increase the manufacturing process and productivity. This will positively influence the demand for FPGA in the region. The growing innovation in wireless communication will contribute to the FPGA market growth in 4G/5G waveform coexistence, non-contiguous carrier aggregation, and processing of centralized Cloud Radio Access Network (C-RAN).
It uses dynamic partial reconfiguration that offers higher flexibility in design time and runtime suitable for 5G architecture. Moreover, these devices are increasingly being adopted by automotive manufacturers and OEMs to build efficient safety systems, such as adaptive cruise control, collision avoidance systems, and Advanced Driver Assistance Systems (ADAS), making them more scalable. They also require the least hardware modifications for system upgrades.
Field Programmable Gate Array (FPGA) Market Segment by Applications can be divided into: Test, Measurement And Emulation; Consumer Electronics; Automotive; Wired and Wireless Communication; Industrial; Military and Aerospace; Health Care; Data Center and Computing; and Telecommunications and others.
FPGA chips are majorly adopted in industries, owing to their ability to market faster and provide cheaper solutions for low to medium volume production, compared to Application-specific Integrated Circuits (ASIC), which are more expensive and time-consuming. Adaptable acceleration in data centers for storage systems and highly efficient servers are projected to drive the market growth. FPGA offers low-latency connection and customized high bandwidth for network and storage systems.
Based on type, the SRAM segment is expected to be the most lucrative. Because it allows for easy reconfiguration, SRAM is the most often used technology for programming FPGAs. SRAM-based FPGAs are created using the CMOS fabrication method, which allows for higher power efficiency and logic density than previous technologies, which is propelling the market forward.
The flash segment of the FPGA market is projected to grow at the highest CAGR during the forecast period. The key factor contributing to the growth of this segment is the nonvolatility and the low power consumption of flash-based FPGA. Moreover, these FPGAs offer resistance to radiation and eliminate the requirement of any external memory. Flash-based FPGA can also be programmed.
Based on application, the data centers & computing segment is expected to be the most lucrative. The continued usage of high-performance computing (HPC) in cloud storage, as well as significant technological breakthroughs in the fields of machine learning, artificial intelligence, and deep learning, are driving this segment’s growth.
The market for telecommunications segment to hold the largest share throughout the forecast period
The telecommunications segment accounted for a high market share, in terms of value, in 2021. The high market share is driven by the increasing adoption of FPGAs across various communication applications, such as optical transport networks (OTN), network processing, wireless baseband, and backhaul solutions.
The re-programmability of FPGAs helps telecom operators to carry out rapid updates to fix system issues or add new features across the telecommunication systems. Adding to this, the expansive penetration of 5G communication infrastructure across developed and emerging economies worldwide will amplify the adoption of FPGAs over the forecast period.
Low-end FPGA segment to dominate market during the forecast period.
The low-end FPGA segment is expected to lead the market during the forecast period. High energy efficiency and reduced complexity of low-end FPGAs have accelerated their adoption across automotive, consumer electronics, and industrial applications.
Several industry participants across the low-end FPGA ecosystem are focusing on organic growth
strategies, such as new product development and launches, to gain competitive benefits in the
market. For instance, in November 2021, Renesas Electronics Corporation (Japan) introduced a new product line of low-end FPGAs with its Forge FPGA Family. New low-end FPGAs are designed for applications that require less than 5,000 logic gates. These FPGAs will have applications in highvolume consumer electronics and IoT devices.
20–90 nm segment is expected to hold high market share from 2022 to 2027.
20–90 nm segment is expected to hold high market share during the forecast period. The high market share is driven by several features offered by the 20–90 nm FPGAs such as high performance, programming flexibility, and low power consumption. FPGAs with node sizes ranging between 20–90 nm have been available in the market for quite some
time, and customers prefer these FPGAs due to their industry’s best value features such as high
bandwidth and reduced total system costs suitable for general purpose and portable applications.
FPGA market in Asia Pacific to grow at highest CAGR during the forecast period. Asia Pacific currently holds the largest share of the market owing to the increasing deployment of 5G
telecommunication networks in Asia Pacific economies, including China, Japan, and South Korea.The FPGA market in China is growing at a fast pace, owing to the presence of established automotive and consumer electronics players in the region. Furthermore, companies, such as Alibaba, Samsung, Xinhua, etc., in this region are heavily investing in AI, contributing to the demand growth for these chips.
According to the July 2022 press release by the Ministry of Industry and Information Technology,
China, the country added 300,000 new 5G base stations in the second quarter of 2022. As of June
2022, China has over 1.85 million active 5G base stations and is aimed to deploy ~2 million 5G base stations by the end of 2022.
FPGAs play a vital role in 5G networks as they offer the greater flexibility and performance required to meet the increasing and ever-changing demand for 5G wireless connectivity. Large-scale deployment of 5G infrastructure across the region will fuel the FPGA market growth over the forecast period.
The APAC FPGA market is likely to be driven by the telecommunications, industrial, automotive, consumer electronics, and computer industries. This growth can be attributed to the increased adoption of IoT and machine-to-machine (M2M) communication in the industrial and automotive sectors. FPGAs offer parallel processing and reprogrammability features, which make them suitable for these applications.
APAC houses some of the major semiconductor foundries such as Taiwan Semiconductor Manufacturing Company (TSMC) (Taiwan), United Microelectronics Corporation (UMC) (Taiwan), and Samsung Foundries (South Korea), which drive the growth of the FPGA market in the region. Moreover, the increasing number of smartphone users in countries such as China and India is expected to drive the growth of the FPGA industry in APAC during the forecast period.
Key players in the FPGA market include companies operating at different stages of the value chain. These companies include Xilinx, Inc. (US); Intel Corporation (US), Microchip Technology Inc. (US); Lattice Semiconductor Corporation (US); QuickLogic Corporation (US); Efinix, Inc. (US); Flex Logic Technologies, Inc. (US); GOWIN Semiconductor Corp. (China); Achronix Semiconductor Corporation (US); S2C, Inc. (US); Leaflabs, LLC (US); Adlec, Inc. (US); BitSim AB (Sweden); ByteSnap Design (UK); Enclustra GmbH (Switzerland); EnSilica (US); Gidel (US); Nuvation Engineering (US); Selexica, Inc. (Germany); and EmuPro Consulting Private Limited (India). These companies focus on adopting both organic and inorganic growth strategies, such as product launches and developments, partnerships, contracts, collaborations, and acquisitions, for strengthening their position in the market.
In conclusion, FPGAs are a versatile and powerful tool for efficient system design. From data centers to military radars and electronic warfare systems, FPGAs offer a range of benefits for high-speed data processing, real-time signal processing, and reliable operation in harsh environments. With their ability to be reprogrammed and updated as the system requirements change, FPGAs offer a flexible and cost-effective solution for a wide range of applications.
FPGAs are being widely used in military applications due to their flexibility, low latency, high reliability, and power efficiency. FPGAs are being used in various military systems, including radar systems, electronic warfare systems, missile systems, and cybersecurity. As military systems become more complex, FPGAs will continue to play a critical role in ensuring their success.