The landscape of technology is evolving rapidly, with the digital transformation across various industries playing a pivotal role in this shiftAs businesses increasingly rely on data centers, artificial intelligence, and machine learning to enhance operations, the demand for advanced computing solutions is surgingAn area that has been gaining significant momentum is the field of Field-Programmable Gate Arrays, commonly known as FPGAsAccording to Frost & Sullivan's projections, the global market for FPGAs is expected to skyrocket to an astonishing $12.58 billion by the year 2025.

In response to this burgeoning demand, manufacturers are emphasizing the development of mid-range FPGAs, with major players like Lattice Semiconductor, Intel, and AMD stepping onto the stage with innovative products that cater to evolving market needsRecently, Lattice Semiconductor unveiled its latest offerings: the Lattice Avant-G™ and Avant-X™ platforms

Advertisements

These new platforms are tailored for general design and advanced interconnect applications, respectively, expanding the company's footprint in the mid-range FPGA arena.

In an exclusive interview, Xuhong Lai, President of Lattice Semiconductor Asia Pacific, articulated his vision of the market's trajectoryHe acknowledged the soaring demands in sectors such as industrial automation, automotive technology, and artificial intelligence, while emphasizing that Lattice will continue to nurture low-end markets as wellHowever, he indicated that the most significant growth is poised to arise from mid-range FPGA advancements in the coming years.

FPGA technology, often less known to the general public, delivers a versatile and programmable solution that distinguishes it from traditional chipsFPGAs can be reconfigured post-manufacturing, enabling users to customize the chip's functionality to meet specific requirements

Advertisements

Unlike CPUs, GPUs, and other fixed-function chips, FPGAs maintain flexibility, allowing developers to design their own circuit configurations using dedicated Electronic Design Automation (EDA) software.

The market for FPGAs can be segmented based on size, power consumption, and performance, categorizing them into small, mid-range, and large variantsThe pricing structure typically reflects these categories; small FPGAs may range from $1 to $10, mid-range options are priced around $50 to $100, while large FPGAs can cost hundreds to thousands of dollars depending on their specifications.

As artificial intelligence and machine learning technologies proliferate, the volume and complexity of data processing demands escalate rapidly, propelling the need for more sophisticated FPGA solutionsConsequently, both domestic and international manufacturers are actively strategizing and repositioning themselves within the mid-range FPGA market

Advertisements

In recent years, Intel has introduced its Agilex FPGA series, followed by AMD's launch of its ACAP platform, displaying the competitive landscape within this domain.

At the end of last year, Lattice made significant strides by releasing its first series of products with over 100K logic elements, aimed squarely at the network edge application marketThis strategic move permitted Lattice to exploit its strengths in low-power architecture, compact size, and high-performance capabilities, signaling a bold entry into the mid-range FPGA sector.

When announcing the Avant platform's debut, Lai remarked, "The launch of the Avant platform not only positions Lattice as a key player in the mid-range FPGA market but also opens a new door to a $3 billion incremental market opportunity.” The momentum has only continued, as Lattice recently introduced its innovative mid-range FPGA products—Avant-G™ and Avant-X™, designed for general use and sophisticated interconnects, respectively

• Kuaishou Restructures with Rotating Leadership
• Slowing Economic Growth in the United States
• A Crucial Deciding Moment for the Stock Market
• LNG Prices Fall on Weak Demand: Rebound Ahead?
• US-China Interest Rate Outlook

This new suite of solutions represents a significant upgrade featuring enhanced capabilities, specifically targeting domains like AI, embedded vision, security, and factory automation.

Lai further elaborated on the changes in demand: as automotive and industrial data throughput grow, existing products no longer suffice for the latest memory interfacesCoupled with the needs prompted by AI computing requirements, Lattice is revising its digital signal processor architecture to ensure low power consumption while optimizing applications in automotive and industrial settings.

The expectation is that mid-range products will increasingly contribute to Lattice's overall revenueProducts launched recently, like the Avant-E, are projected to experience sales growth in 2024, amplifying the anticipated success of Avant-G and Avant-XHowever, Lai highlights that meeting the hardware challenge involves more than just product development; it necessitates an alignment of development tools and software IP with customer needs, making for a learning curve and adaptation phase between the products and market requirements.

As we cascade into the era of artificial intelligence, a multitude of opportunities arises

AI chips, comprised mainly of graphics processing units (GPUs), FPGAs, and application-specific integrated circuits (ASICs), demand high multi-core processing, concurrent task handling, and extensive bandwidthThese AI chips, also referred to as AI accelerators or compute cards, are specifically engineered to tackle the substantial computational workloads associated with AI applications.

Currently, NVIDIA commands an astonishing 95% market share in AI training, creating a high barrier to entry for competitorsHowever, geopolitical tensions and surging computing demands have led to challenges in obtaining NVIDIA GPUs, coupled with escalating costs for AI computationThis environment has prompted industry giants such as Google, Amazon, Alibaba, Tencent, and Meta to embark on their paths of developing proprietary AI chips.

Notably, these circumstances also present a unique opportunity for other types of AI chips beyond GPUs

Lai views the restrictions on technology and supply chains as fortuitous for FPGAs, primarily due to their architectural advantages in AI training applicationsHe points out that not all use cases necessitate GPUs; particularly in edge computing scenarios, FPGAs can serve as viable alternatives, optimizing AI computational needs more effectively along with diverse device integration.

It's essential to clarify that the relationship between FPGAs and GPUs should not be viewed as strictly binary opposition"FPGA applications and GPUs coexist as cooperative processors," stated Puxiaoshuang, Lattice’s Director of Technical SupportHe elaborated that in edge AI applications, the FPGA can supplement the functions of the main GPU, allowing for optimized power usage while ensuring necessary alerts and notifications occur during critical timesWhile GPUs can handle these tasks, laptops often conserve battery life by limiting GPU activation; hence, FPGAs play a significant role in this seamless collaboration rather than competition.