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What is the Addressable Market Opportunity for “Hybrid Memory Cube (HMC) and High-bandwidth Memory (HBM)”?

The global Hybrid Memory Cube (HMC) and High-Bandwidth Memory (HBM) market is projected to reach US$4.7 billion by 2025, driven by the blistering pace of growth of AI-assisted technologies, increase in AI workloads and the ensuing need for more memory in AI servers.

Global Industry Analysts, Inc. (GIA) launches comprehensive analysis of industry segments, market trends, growth drivers, market share, size and demand forecasts on the global Hybrid Memory Cube (HMC) and High-bandwidth Memory (HBM) market. Report segmentation includes Application (Graphics, High-performance Computing, Networking, Data Centers); Memory Type (HMC, HBM); and Product type (GPU, CPU, APU, FPGA, ASIC).

14 June 2:58 A.M., California/Marketwire/ - According to the new market research report, the global Hybrid Memory Cube (HMC) and High-Bandwidth Memory (HBM) market is projected to reach US$4.7 billion by 2025, driven by the blistering pace of growth of AI-assisted technologies, increase in AI workloads and the ensuing need for more memory in AI servers. Making data readily available for AI initiatives is key for successful AI projects and this requires data to be stored closer to the processing tasks to speed up data processing and deliver business value by providing timely and actionable insights. On an average, AI servers require over 8 times the amount of DRAM capacity and over three times the amount of SSDs when compared to a traditional server. This need for memory will only grow bigger and more urgent with the growth of deep learning, machine learning, expanding size of neural networks and emergence of newer and more complex neural networks such as Feedforward Neural Network, Radial basis function Neural Network, Kohonen Self Organizing Neural Network, Recurrent Neural Network (RNN), Convolutional Neural Network and Modular Neural Network. For instance, Machine Learning (ML) involves continuous running of algorithms against historical data, creating a hypothesis, analyzing new data in real-time as and how it is generated and fed through the IoT system.

Similarly, in Deep Learning incoming processed data sets are used to train multi-layered neural networks to continuously learn to interpret data with greater speed and accuracy. To achieve all of these with efficiency and effectiveness algorithms need dynamic on-the-go access to cold (old historic data), warm (recently generated data) and hot (current sensor generated data). AI and machine learning have changed the computing paradigm. Execution time of a program now depends on memory transfers rather than processors thereby creating the need for greater memory bandwidth. The scenario is priming the in-memory computing paradigm. In other words, lines between memory and compute are rapidly blurring with AI and machine learning requiring memory-rich processing and compute-capable memory. Gaining new interest is Hybrid Memory Cube (HMC) which is defined as next generation high-performance RAM interface for TSV-based stacked DRAM memory.

Given that AI requires cold data buried in SSDs, the high memory density of HMC enables cold data to be readily usable by transferring it to the RAM (hot data). Benefits of HMC include higher bandwidth (upto 400 GB/s); increased power efficiency; lower system latency; lower energy used; increased request rate for multiple cores; and greater memory packing density. The United States and Europe represent large markets worldwide with a combined share of 73.4%. China ranks as the fastest growing market with a 36.2% CAGR over the analysis period supported by the countrys herculean efforts to challenge the world and especially the U.S in the AI race. The National Development and Reform Commission (NDRC) remains committed to encourage R&D in AI and machine learning. Giants such as Baidu, Alibaba, Tencent, and Huawei are actively involved and committed to AI R&D. Against this backdrop as AI ecosystems evolve and proliferate, enabling hardware like memory chips and processors will witness robust growth in the country.

Key Competitors Covered in the Report
Advanced Micro Devices, Inc.
Arira Design
ARM Ltd.
Cadence Design Systems, Inc.
Cray, Inc.
Fujitsu Ltd.
IBM Corporation
Intel Corporation
Marvell Technology Group Ltd.
Micron Technology, Inc.
NVIDIA Corporation
Open-Silicon, Inc.
Rambus, Inc.
Samsung Electronics Co., Ltd.
SK Hynix, Inc.
Xilinx Inc.

Geographies Analyzed in the Report
United States
Canada
Japan
China
Europe (France, Germany, Italy, United Kingdom, and Rest of Europe)
Asia-Pacific
Rest of World

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Research Methodology
This latest edition of the research study is conducted and published by Global Industry Analysts, Inc., in close collaboration with senior executives in the industry driving strategy, business development, marketing, sales, product management, technology and operations. All analysis and findings published in the report are based on validated engagements from a total executive pool size of 5832. Among this pool, 933 direct interactions with domain experts were carried out via our proprietary market research platform, MarketGlass. Among the 173 unique participations, a total of 78 validated responses were received as part of this report's primary research outreach program. We are unique in the industry to provide our clients with the validated list executive engagements and the complete project data stack.

About Global Industry Analysts, Inc.
Global Industry Analysts, Inc., (GIA) (www.strategyr.com) is the world's only influencer driven AI powered market research company. Serving more than 41,000 clients from 36 countries, GIA is recognized for accurate forecasting of markets and industries for 33 years, offering the widest coverage of topics, geographic markets, competitive brands, and companies profiled.

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