FPGA 가속화용 HBM 시장 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the HBM for FPGA acceleration market size is expected to increase from USD 100.11 million in 2025 to USD 130.27 million in 2026 and reach USD 490.79 million by 2031, growing at a CAGR of 30.38% over 2026-2031.

This report is Segmented by Memory Type (HBM2E, HBM3, HBM3E, and HBM4), Integration Type (FPGA SoCs With Integrated HBM, and More), Application (AI Inference Acceleration, High-Performance Computing, and More), End User (Hyperscalers and Cloud Service Providers, and More), and Geography (North America, Asia-Pacific, and Middle East and Africa). The Market Forecasts are Provided in Terms of Value (USD).

Global HBM For FPGA Acceleration Market Trends and Insights

Rising Deployment of HBM-Enabled FPGA Cards in Cloud and Edge Accelerators

Cloud and edge systems are moving toward denser data paths, and that shift is making DDR-based FPGA designs less attractive in the most bandwidth-heavy environments. DYNANIC and Silicom demonstrated a 400G FPGA-based AI networking setup in September 2025 that paired Altera Agilex 7 M-Series silicon with HBM2e for low-latency packet handling in AI fabrics. Silicom's ThunderFjord card demonstrated how an HBM-equipped board can support up to 32GB of HBM2e and 2 X 2.6Tbps of bandwidth in a form factor designed for high-speed data center networking. Altera also positions the Agilex family for data center acceleration use cases that need programmable logic, high memory throughput, and deployment flexibility across cloud infrastructure. This makes the HBM for FPGA acceleration market more dependent on card and module vendors that can package complete solutions rather than only supply chips. It also means that design wins in networking and inference can carry over into adjacent edge applications that require similar bandwidth behavior.

Growing Need for Deterministic, Low-Latency Memory Access in Real-Time Workloads

The HBM for FPGA acceleration market is benefiting from workloads that value timing consistency as much as throughput. In FPGA-based designs, memory channels can be assigned in hardware, which helps keep response behavior more predictable than in shared compute environments. AMD stated that its Alveo UL3422 accelerator achieved latency below 3 ns for electronic trading workloads, demonstrating that FPGA-based acceleration still plays a strong role in extremely low-latency settings. A 2025 arXiv paper on the RoCE BALBOA stack also showed direct HBM channel use for payload staging on data center FPGAs, achieving 100G throughput comparable to commercial NICs. The addressable demand base is therefore widening beyond classic trading applications into AI fabric control, packet inspection, and other services where jitter can hurt system performance. As these use cases expand, the HBM for FPGA acceleration market gains support from buyers willing to pay more for consistent timing behavior.

Limited Advanced Packaging Capacity for FPGA-HBM Integration

The HBM for FPGA acceleration market still depends on advanced packaging flows that are harder to scale than standard board-level memory designs. HBM integration requires close coupling between the compute die, the memory stack, and the interconnect structure, so product timing can be affected by packaging availability even when logic demand is strong. AMD announced more than USD 10 billion in investments in Taiwan's ecosystem in May 2026 to expand advanced packaging manufacturing for AI infrastructure, underscoring how central packaging capacity has become across accelerator supply chains. Samsung's HBM4 ramp and Micron's HBM4 production progress also show that memory and packaging readiness now move together rather than as separate procurement steps. For FPGA vendors, this raises the importance of early planning and narrows the room for short-cycle volume expansion. The result is a market where qualified supply can remain tighter than end-user interest for longer periods.

Other drivers and restraints analyzed in the detailed report include:

1. Hyperscaler Shift Toward FPGA-Based Custom Acceleration for Select Workloads
2. Wider Availability of HBM3 and HBM3E in High-End FPGA Platforms
3. High Bill-of-Materials Cost Compared With GDDR- and DDR-Based FPGA Designs

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

HBM2E held 65.83% of the HBM for FPGA acceleration market share in 2025, reflecting the strength of current installed platforms and the slower replacement cycle for qualified accelerator designs. Altera's Agilex 7 M-Series integrates up to 32GB of HBM2e in a single device and provides up to 820GB/s of peak bandwidth, helping make HBM2E the practical baseline for shipping products. That installed base matters because buyers in network, telecom, and infrastructure roles often keep the same hardware generation in service longer than hyperscale compute buyers. HBM3 remained a bridge tier in the segment because supply and platform planning moved quickly toward the next step in the memory roadmap. HBM3E is projected to grow at a 31.18% CAGR through 2031, reflecting stronger supplier focus, higher data rates, and better alignment with next-wave accelerator requirements.

JEDEC's JESD235 standard family continues to support interoperability across HBM generations and helps shorten qualification work when vendors move between memory sources within shared design rules. Siemens said HBM3E has entered high-volume production across the AI accelerator ecosystem, and it also pointed to custom HBM4 base-die approaches as a future area of product differentiation. Samsung's HBM4 shipment milestone and Micron's HBM4 production progress show that the memory roadmap is moving faster than many FPGA product cycles, potentially shifting value toward vendors with stronger transition planning. The near-term HBM for FPGA acceleration market still centers on HBM2E shipments, but future platform roadmaps are increasingly being shaped by HBM3E readiness and the first HBM4 design paths.

Standalone FPGA Accelerator Cards with HBM held 53.18% of the HBM for FPGA acceleration market share in 2025, reflecting the maturity of PCIe-based deployment in enterprise and colocation environments. Card-based designs remain easier to qualify, easier to swap into existing servers, and easier for board partners to tailor around specific workloads. Silicom's ThunderFjord product shows how current card designs can package HBM2e, high port throughput, and data center networking features into a familiar accelerator format. This is why standalone cards still anchor the commercial base of the HBM for FPGA acceleration market, even as newer module formats gather attention. PCIe card deployments also fit the procurement style of system integrators that need incremental upgrades rather than full rack redesigns.

OCP/OAM FPGA Accelerator Modules are projected to expand at 31.08% CAGR through 2031 as hyperscaler environments shift toward shared chassis and more flexible accelerator pools. Altera's data center positioning supports this path by aligning programmable acceleration with rack-scale AI systems and open module deployment models. The March 2026 Altera and Arm collaboration also points to tightly integrated systems in which CPU, FPGA, and memory resources are planned together from the start. FPGA SoCs with integrated HBM and smaller PCIe modules will remain important in select designs, but the long-term direction for HBM in the FPGA acceleration market is toward module-based deployment in larger AI and networking fabrics.

Complete Report Scope:

• By Memory Type
  • HBM2E
  • HBM3
  • HBM3E
  • HBM4
• By FPGA Integration Type
  • Standalone FPGA Accelerator Cards with HBM
  • FPGA SoCs with Integrated HBM
  • PCIe FPGA Accelerator Modules
  • OCP/OAM FPGA Accelerator Modules
• By Application
  • AI Inference Acceleration
  • High-Performance Computing
  • Network Acceleration
  • Financial Services and Low-Latency Trading
  • Defense, Aerospace, and Secure Systems
  • Scientific and Industrial Simulation
• By End User
  • Hyperscalers and Cloud Service Providers
  • Enterprise OEMs and System Integrators
  • Telecom and Networking Operators
  • Defense and Government Organizations
  • Financial Institutions
  • Research Institutes and Laboratories
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • Taiwan
    • India
    • Rest of Asia-Pacific
  • South America
  • Middle East and Africa

Geography Analysis

North America held 44.94% of the HBM for FPGA acceleration market share in 2025, making it the largest regional contributor to current revenue. The region benefits from a dense concentration of FPGA design teams, AI infrastructure spending, and system-level integration capabilities. Altera's data center positioning and its collaboration with Arm both reinforce North America's role as a base for programmable acceleration in AI server environments. AMD's May 2026 commitment of more than USD 10 billion across the Taiwan ecosystem also reflected how North American accelerator demand is directly linked to upstream packaging and memory capacity in Asia. Financial services and low-latency infrastructure deployments add a premium demand layer in the United States, supporting continued use of FPGA-based acceleration for specialized workloads.

Asia-Pacific is projected to expand at a 31.36% CAGR through 2031, making it the fastest-growing geography in the HBM for FPGA acceleration market. The region combines memory manufacturing, deep packaging, electronics production, and rising AI data center demand within a single broad supply ecosystem. SK hynix said HBM3E was expected to account for nearly two-thirds of total HBM shipments in 2026, and Samsung reported HBM4 mass production shipment in February 2026, both of which underline South Korea's importance in supply availability. Micron's progress in HBM4 production also strengthens Asia-Pacific's role in the next stage of memory supply for advanced accelerator platforms. Taiwan remains critical because advanced packaging capacity there affects how quickly HBM-enabled systems can move from design to commercial shipment. Japan's focus on semiconductor capacity and its role in memory expansion further support the region's long-term weight in the HBM for FPGA acceleration market.

Europe, South America, and Middle East and Africa together account for a smaller share of current revenue, but each remains relevant for selected deployment paths. Europe matters most for defense, telecom, and industrial electronics applications, where programmability and secure processing remain important. The EU Chips Act commitment of EUR 43 billion (USD 48.6 billion) through 2030 could improve regional semiconductor capabilities over time, even though dependence on advanced packaging remains high today. South America, the Middle East, and Africa are still early-stage opportunities, and growth there is more closely tied to broader cloud investment and sovereign AI buildouts than to immediate HBM platform volume. These regions, therefore, contribute less to current sales, but they still expand the future opportunity set for HBM in the FPGA acceleration market.

1. SK hynix Inc.
2. Samsung Electronics Co., Ltd.
3. Micron Technology, Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising Deployment of HBM-Enabled FPGA Cards In Cloud And Edge Accelerators
  • 4.2.2 Growing Need For Deterministic, Low-Latency Memory Access In Real-Time Workloads
  • 4.2.3 Hyperscaler Shift Toward FPGA-Based Custom Acceleration For Select Workloads
  • 4.2.4 Wider Availability Of HBM3 And HBM3E In High-End FPGA Platforms
  • 4.2.5 Increasing Importance Of Power-Efficient Bandwidth Scaling Versus Pure Compute Scaling
  • 4.2.6 Co-Optimization Of FPGA And HBM In Heterogeneous AI Inference Pipelines
• 4.3 Market Restraints
  • 4.3.1 Limited Advanced Packaging Capacity For FPGA-HBM Integration
  • 4.3.2 High Bill-Of-Materials Cost Compared With GDDR- And DDR-Based FPGA Designs
  • 4.3.3 Thermal And Board-Level Design Complexity In HBM-Enabled Accelerator Systems
  • 4.3.4 Supply Concentration In HBM Manufacturing And Interposer Ecosystems
• 4.4 Industry Value Chain Analysis
• 4.5 Impact Of Macroeconomic Factors On The Market
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Bargaining Power Of Suppliers
  • 4.8.2 Bargaining Power Of Buyers
  • 4.8.3 Threat Of New Entrants
  • 4.8.4 Threat Of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Memory Type
  • 5.1.1 HBM2E
  • 5.1.2 HBM3
  • 5.1.3 HBM3E
  • 5.1.4 HBM4
• 5.2 By FPGA Integration Type
  • 5.2.1 Standalone FPGA Accelerator Cards with HBM
  • 5.2.2 FPGA SoCs with Integrated HBM
  • 5.2.3 PCIe FPGA Accelerator Modules
  • 5.2.4 OCP/OAM FPGA Accelerator Modules
• 5.3 By Application
  • 5.3.1 AI Inference Acceleration
  • 5.3.2 High-Performance Computing
  • 5.3.3 Network Acceleration
  • 5.3.4 Financial Services and Low-Latency Trading
  • 5.3.5 Defense, Aerospace, and Secure Systems
  • 5.3.6 Scientific and Industrial Simulation
• 5.4 By End User
  • 5.4.1 Hyperscalers and Cloud Service Providers
  • 5.4.2 Enterprise OEMs and System Integrators
  • 5.4.3 Telecom and Networking Operators
  • 5.4.4 Defense and Government Organizations
  • 5.4.5 Financial Institutions
  • 5.4.6 Research Institutes and Laboratories
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 Europe
    • 5.5.2.1 Germany
    • 5.5.2.2 United Kingdom
    • 5.5.2.3 France
    • 5.5.2.4 Italy
    • 5.5.2.5 Rest of Europe
  • 5.5.3 Asia-Pacific
    • 5.5.3.1 China
    • 5.5.3.2 Japan
    • 5.5.3.3 South Korea
    • 5.5.3.4 Taiwan
    • 5.5.3.5 India
    • 5.5.3.6 Rest of Asia-Pacific
  • 5.5.4 South America
  • 5.5.5 Middle East and Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Products and Services, Recent Developments)
  • 6.4.1 SK hynix Inc.
  • 6.4.2 Samsung Electronics Co., Ltd.
  • 6.4.3 Micron Technology, Inc.
• 6.5 Other Ecosystem Players
  • 6.5.1 Advanced Micro Devices, Inc.
  • 6.5.2 Intel Corporation
  • 6.5.3 Lattice Semiconductor Corporation
  • 6.5.4 Microchip Technology Incorporated
  • 6.5.5 Achronix Semiconductor Corporation
  • 6.5.6 QuickLogic Corporation
  • 6.5.7 Efinix, Inc.
  • 6.5.8 GOWIN Semiconductor Corporation
  • 6.5.9 Flex Logix Technologies, Inc.
  • 6.5.10 NVIDIA Corporation
  • 6.5.11 Xilinx, Inc.
  • 6.5.12 TSMC
  • 6.5.13 Amkor Technology, Inc.
  • 6.5.14 ASE Technology Holding Co., Ltd.
  • 6.5.15 Cadence Design Systems, Inc.
  • 6.5.16 Synopsys, Inc.
  • 6.5.17 Broadcom Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment