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

According to Mordor Intelligence, the HBM for HPC and supercomputing market size is expected to increase from USD 0.60 billion in 2025 to USD 0.76 billion in 2026 and reach USD 2.01 billion by 2031, growing at a CAGR of 21.47% over 2026-2031.

This report is Segmented by HBM Generation (HBM3, HBM3E, and HBM4, and More), Memory Capacity (Up To 8 GB, 8-16 GB, and More), Processor Interface (GPU-Based HPC Processors, CPU-Based HPC Processors, and More), Application (Scientific Computing, Weather and Climate Modeling, and More), and Geography (North America, Asia-Pacific, and More). The Market Forecasts are Provided in Terms of Value (USD).

Global HBM For HPC and Supercomputing Market Trends and Insights

Accelerating AI Training And Supercomputing Demand

The HBM for HPC and supercomputing market is benefiting from the growing overlap between generative AI training and classical simulation, as both workloads now compete for the same memory-intensive compute clusters. SK hynix says the current memory cycle is being led by HBM demand, tying that momentum to the production ramp of platforms that use HBM3E and HBM4 at scale. NVIDIA now positions Vera Rubin for scientific computing as well as AI, with Los Alamos systems such as Mission, Vision, and Veritas set to combine Rubin GPUs with Vera CPUs for open and classified workloads. This broadens the HBM's buyer base in the HPC and supercomputing market beyond commercial cloud into national laboratory and sovereign compute programs. It also means suppliers are serving a demand pool supported by both model training scale and the growing use of AI models in simulation workflows.

HBM3E And HBM4 Adoption In Next-Gen Accelerators

The HBM for HPC and supercomputing market is also being driven by the move from HBM3 to HBM3E and HBM4, as the shift changes both bandwidth and capacity at the platform level. Samsung began HBM4 mass production in February 2026 and said its new stack reaches 11.7 Gbps and 3.3 TB/s per stack, marking a clear performance step over prior generations. NVIDIA says each Vera Rubin R200 GPU features 288 GB of HBM4 and delivers 22 TB/s of memory bandwidth, locking system designers into a new memory generation rather than a minor upgrade path. In the HBM market for HPC and supercomputing, this means procurement timing is increasingly tied to HBM allocation schedules rather than just processor availability. Export rules tied to advanced HBM performance thresholds also narrow the qualified end-user base for the most advanced configurations, reinforcing concentration among approved buyers and supply routes.

Limited HBM Supply And Long Qualification Cycles

The HBM for HPC and supercomputing market remains constrained by qualification cycles that are much longer than standard DRAM ramps, especially as stack heights rise. Samsung's own patent work on dummy die structures for future high-stack designs indicates severe yield pressure in 16-layer designs, with reported losses of 40%-60% compared to 8-layer designs. Micron says fiscal 2026 capital expenditure is expected to exceed USD 25 billion, indicating how much spending remains before supply relief becomes meaningful. For the HBM market in HPC and supercomputing, these long cycles translate into configuration lock-in risk, as systems ordered under one memory roadmap may face timing or specification changes before delivery.

Other drivers and restraints analyzed in the detailed report include:

1. Memory-Bound Workloads In HPC Clusters
2. Co-Packaged Memory Architectures In Exascale Systems
3. Extreme Dependence On A Few Qualified Memory Suppliers

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

Segment Analysis

HBM3 held 53.18% of the HBM for the HPC and supercomputing market in 2025, reflecting the installed base of Hopper-era systems purchased through 2024 and 2025. HBM2 and HBM2E remained present in legacy clusters, but their roles continued to shrink as operators began upgrading capabilities across flagship systems. HBM3E emerged as the transition layer for HBM in the HPC and supercomputing markets, bridging current deployment cycles with the upcoming move to HBM4. SK hynix says HBM3E will continue to account for a large share of total HBM shipments through 2026, which supports that transition view.

HBM4 is the fastest-growing generation with a 22.29% CAGR from 2026 to 2031, and that rise is tied directly to NVIDIA Vera Rubin and AMD Instinct MI455X configurations. Samsung says its HBM4 mass production uses a 6th-generation 1c DRAM die and can scale from 11.7 Gbps to 13 Gbps, indicating the product line is already being designed for a further speed step. The HBM for HPC and supercomputing industry is therefore moving through a compressed roadmap, because HBM4E samples aimed at 16-layer and 48 GB configurations had already entered customer sampling by mid-2026. In the HBM for HPC and supercomputing market, that compression raises capital planning pressure on integrators, because each generation now has a shorter stable window before the next one enters qualification.

The 16 GB to 32 GB tier accounted for 48.63% of the HBM market share in the HPC and supercomputing market in 2025, as 8-high HBM3 and HBM3E stacks remained the main volume configuration across leading accelerator platforms. That tier should remain the primary shipment base in the near-term transition, as Blackwell Ultra and comparable systems are still ramping in volume. At the same time, the HBM for the HPC and supercomputing market is shifting toward denser stacks as both performance and total memory per package rise. This keeps the middle tier important in the current cycle, even as buyer attention shifts toward higher densities.

The Above 32 GB band is set to grow at a 22.21% CAGR from 2026 to 2031, driven by designs such as NVIDIA Vera Rubin R200 and AMD MI455X that require much larger per-GPU memory pools. A 2025 peer-reviewed study found that hybrid bonding in 3D-stacked HBM creates increasing thermal and mechanical stress at 12+ layers, which explains why this part of the HBM for the HPC and supercomputing market faces both strong demand and significant process risk. Lower-capacity tiers still matter in the HBM for HPC and supercomputing markets, including edge HPC, FPGA deployments, and embedded simulation systems, where power limits matter more than absolute capacity. Standards compliance also remains important across all tiers, as interoperability decisions must still align with formal HBM interface specifications and packaging rules.

Complete Report Scope:

• By HBM Generation
  • HBM2 and HBM2E
  • HBM3
  • HBM3E
  • HBM4
• By Memory Capacity Per Stack
  • Up to 8 GB
  • 8 GB to 16 GB
  • 16 GB to 32 GB
  • Above 32 GB
• By Processor Interface
  • GPU-based HPC Processors
  • CPU-based HPC Processors
  • AI Accelerators and Custom ASICs
  • FPGA-based Accelerators
• By Application
  • Scientific Computing
  • Weather and Climate Modeling
  • Defense and National Security Computing
  • Engineering Simulation and Digital Twins
  • AI-enabled HPC Workloads
• 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 43.39% of the HBM market share for the HPC and supercomputing market in 2025, making it the largest regional base for current deployments. The region's lead reflects the concentration of national laboratories, hyperscalers, and advanced computing procurement programs that already buy memory-rich architectures at scale. Aurora at Argonne and the planned Doudna system at NERSC show how the HBM for the HPC and supercomputing market in North America is tied to very large public computing programs with long buying cycles. Export control rules under ECCN 3A090.c also shape the HBM for the HPC and supercomputing markets in this region, because the most advanced configurations are closely tied to compliance and allied-country access. Demand visibility is therefore stronger in North America than in many other regions, since agencies such as DARPA and NNSA continue to support multiyear compute programs.

Europe remained smaller in 2025, but its role in the HBM for HPC and supercomputing market is rising with new EuroHPC spending. JUPITER in Germany and Alice Recoque in France reflect a clear scale-up in European HBM use, especially for climate research, AI training, and quantum-oriented simulation workloads. HLRS Stuttgart's HammerHAI and NVIDIA's broader EuroHPC-linked plans show that the HBM for HPC and supercomputing market in Europe is moving from selective adoption to wider institutional rollout. Data sovereignty and certification requirements also matter more here, which adds a compliance layer to memory sourcing and system design.

Asia-Pacific is projected to grow at a 22.34% CAGR from 2026 to 2031, which makes it the fastest-growing regional part of the HBM for HPC and supercomputing market. The region has a dual role, because it is both the main production base for HBM and a growing demand center for sovereign AI and HPC programs. Samsung and SK hynix announced combined regional investment of KRW 240 trillion (USD 168.8 billion) in July 2026, including Samsung's KRW 56 trillion (USD 39.4 billion) and SK hynix's KRW 20 trillion (USD 14.1 billion), which shows how much new capacity and packaging depth are being directed into the supply side. Japan also backed Micron's Hiroshima expansion with JPY 500 billion (USD 3.3 billion) in support, while the facility investment itself was stated at USD 9.3 billion and is aimed at future HBM shipments around 2028 UPI. China remains smaller by current HBM consumption, but domestic HBM efforts could become a stronger variable over the next 3-4 years if technology gaps narrow and export control workarounds remain contested.

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 Accelerating AI Training and Supercomputing Demand
  • 4.2.2 HBM3E and HBM4 Adoption in Next-Gen Accelerators
  • 4.2.3 Memory-Bound Workloads in HPC Clusters
  • 4.2.4 Co-Packaged Memory Architectures in Exascale Systems
  • 4.2.5 Export-Control-Driven Localization of Advanced Memory Supply Chains
  • 4.2.6 Yield Improvement Through TSV and Advanced Packaging Automation
• 4.3 Market Restraints
  • 4.3.1 Limited HBM Supply and Long Qualification Cycles
  • 4.3.2 Extreme Dependence on A Few Qualified Memory Suppliers
  • 4.3.3 Thermal Density and Power Integrity Constraints in Dense Stacks
  • 4.3.4 High Cost Per Bit Versus Alternative Memory Architectures
• 4.4 Industry Supply 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 HBM Generation
  • 5.1.1 HBM2 and HBM2E
  • 5.1.2 HBM3
  • 5.1.3 HBM3E
  • 5.1.4 HBM4
• 5.2 By Memory Capacity Per Stack
  • 5.2.1 Up to 8 GB
  • 5.2.2 8 GB to 16 GB
  • 5.2.3 16 GB to 32 GB
  • 5.2.4 Above 32 GB
• 5.3 By Processor Interface
  • 5.3.1 GPU-based HPC Processors
  • 5.3.2 CPU-based HPC Processors
  • 5.3.3 AI Accelerators and Custom ASICs
  • 5.3.4 FPGA-based Accelerators
• 5.4 By Application
  • 5.4.1 Scientific Computing
  • 5.4.2 Weather and Climate Modeling
  • 5.4.3 Defense and National Security Computing
  • 5.4.4 Engineering Simulation and Digital Twins
  • 5.4.5 AI-enabled HPC Workloads
• 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 NVIDIA Corporation
  • 6.5.2 Advanced Micro Devices, Inc.
  • 6.5.3 Intel Corporation
  • 6.5.4 Fujitsu Limited
  • 6.5.5 IBM Corporation
  • 6.5.6 Broadcom Inc.
  • 6.5.7 Marvell Technology, Inc.
  • 6.5.8 Qualcomm Incorporated
  • 6.5.9 Rambus Inc.
  • 6.5.10 Kioxia Corporation
  • 6.5.11 ASML Holding N.V.
  • 6.5.12 Lam Research Corporation
  • 6.5.13 Applied Materials, Inc.
  • 6.5.14 Tokyo Electron Limited
  • 6.5.15 ASE Technology Holding Co., Ltd.
  • 6.5.16 TSMC
  • 6.5.17 Amkor Technology, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment