AI is a predominant concept, which refers to the phenomenon of a machine exhibiting human intelligence, such as reasoning, learning, self-correcting, adapting, and others. AI is one of the fastest-growing technologies over the years. Continuous efforts and developments to manufacture more human-like robots and increase in their rate of deployment in the developing regions have transformed the overall market. An AI FPGA is an electronic integrated circuit that is configured or designed by the customer after manufacturing. That’s why, it is “field programmable”. FPGAs are totally distinct from CPUs and GPUs in terms of efficiency and performance.
Why do we require FPGAs?
Today’s modern era is a world of digital electronic systems. The demand of AI-based chips has been increasing across the market. This technology has been revolutionizing the face of the electronics market. Memory, microprocessors, and logic gates are the basic requirements for the storage, program execution, device-to-device interfaces, signal processors, and others. In the earlier days, large-scale integrated circuits (LSI) were used in a majority of systems. Later, inventors came up with the idea of custom ICs. These custom ICs eliminate a large number of interconnections and hence reduce system complexity. However, they pose considerable hurdle for vendors, owing to the high-cost involvement in design and development, which results into high manufacturing cost for the products.
So, FPGAs were developed as an alternative for custom ICs.
What makes FPGAs more advantageous?
An FPGA enables to run a simulation in an application-specific integrated circuit (ASIC) in many networking applications. The key advantages of using an FPGA in any application versus an ASIC are:
- faster time-to-market – no layout, mask steps
- no upfront non-recurring expenses (NRE)
- simpler design cycle (the software handles routing)
- more predictable project cycle (owing to elimination of potential re-spins and wafer capacities, and others)
- field programmability – customers remotely program an FPGA even on a daily basis
Deloitte Global predicts that by the end of 2018, over 25 percent of all chips used to accelerate machine learning (ML) in the data center will be FPGAs and ASICs. These new kinds of chips should increase dramatically the use of ML, enabling applications to consume less power and become more responsive, flexible, and capable simultaneously, which would expand the addressable market.
Yes, it can be CUSTOMIZED
Customization of software is done at three levels:
- Chip level
- Server node level
- Data center level
Data center level customization holds a great potential in the coming future. It acts as an accelerator similar to a GPU. Microsoft was the first to use a FPGA, owing to the requirement of scalability for the deep learning infrastructure.
Gaining popularity among INDUSTRY VERTICALS:
An AI FPGA has a prominent place in the semiconductor chip market. The FPGA is a programmable logic device, which is used for a variety of end-market applications in retail, ad servicing technology, agriculture, automotive, education, manufacturing, healthcare, and others.
Because of their reprogrammable nature, FPGAs are widely adopted across many markets. Xilinx, Inc. is an industry leader offering comprehensive solutions constituting FPGA devices, configurable and ready-to-use IP cores, and advanced software for markets and applications, such as aerospace & defense, audio, ASIC prototyping, automotive, consumer electronics, broadcast & pro A/V, data center, medical, industrial, high performance computing and data storage, wired & wireless communications, and others. In December 2015, Intel completed the acquisition of Altera. Moreover, in November 2017, Xilinx, Inc. introduced FPGA solutions to accelerate cloud machine vision, computing, 5G, and IoT. In addition, in October 2016, Microsoft began to deploy Altera’s FPGA accelerator for its Azure and Bing search engines. Furthermore, iFlytek successfully launched a speech recognition solution using Altera’s FPGA chip. In September 2017, Amazon and Xilinx delivered new FPGA solutions and simplified the creation of the acceleration IP and also the tool to manage machine images. Xilinx announced its project, Everest, 7nm FPGA SoC hybrid, in March 2018. This includes the adaptive compute acceleration platform, a high-performing, next-generation programmable logic along with real-time processors, application processors, programmable IO, and a custom network on-chip.
Thus, the vendors have been investing a huge amount in developing efficient products across the globe. Thus, the AI FPGA will create a huge return on investment in the coming future and accelerate the whole digital electronics industry with double-digit growth rate.
We provide syndicated and customized reports on various domains, and recently, we have published our report on the AI Chip Market. Allied Market Research is a full-service market research and business-consulting wing of Allied Analytics LLP, based in Portland, Oregon. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of “Market Research Reports” and “Business Intelligence Solutions”. AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.