Global Computing in Memory Technology Supply, Demand and Key Producers, 2026-2032
Description
The global Computing in Memory Technology market size is expected to reach $ 7398 million by 2032, rising at a market growth of 41.7% CAGR during the forecast period (2026-2032).
As a new computing architecture, storage-computing integration is considered to be a revolutionary technology with potential and has received great attention at home and abroad. The core is to fully integrate storage and computing, effectively overcome the bottleneck of the von Neumann architecture, and combine advanced packaging and new storage devices in the post-Moore era to achieve an order of magnitude improvement in computing energy efficiency.
According to the distance between storage and computing, the technical solutions of generalized storage-computing integration are divided into three categories, namely, Processing Near Memory (PNM), Processing ln Memory (PlM) and Computing in Memory (CIM). In-memory computing is storage-computing integration in a narrow sense.
Global key players of Computing in Memory Technology include Syntiant, Zhicun(Witmem) Technology, Reexen Technology, Graphcore and Mythic, etc. The top five players hold a share over 80%. North America is the largest market, has a share about 50%. In terms of product type, In-memory Computing is the largest segment, occupied for a share of about 88%, and in terms of application, Small Computing Power has a share about 90 percent.
Analysis of the market drivers of Processing-in-Memory (PIM) technology,
1. Explosive growth in computing power demand: the underlying pressure of AI and big data
Demand for AI training and reasoning:
The global AI chip market is expected to reach US$120 billion in 2025, of which 75% of computing power is consumed in data transfer (not computing itself).
Large-scale language models (such as GPT-5) have more than 10 trillion parameters, and processing-in-memory (PIM) can improve the efficiency of sparse matrix operations by 3-5 times.
Data center energy consumption crisis:
Global data center power consumption accounts for 1.5% of total power demand, and data transfer energy consumption accounts for 40% in traditional architectures. Processing-in-Memory (PIM) can reduce energy consumption by more than 50% by reducing the memory wall effect.
2. Moore's Law slows down: an inevitable choice for architectural innovation
Process bottleneck:
The cost of advanced processes (below 3nm) has soared, and the marginal benefits of increasing transistor density have diminished. Processing-in-Memory integrates computing units through 3D stacking processes (such as HBM3) to break through the limitations of planar processes.
Heterogeneous computing needs:
Scenarios such as AI and graphics processing require customized computing units. Storage and computing integration supports the collaborative design of the logic layer and the storage layer to improve the efficiency of dedicated accelerators.
3. New storage technologies mature: hardware foundation is ready
Non-volatile memory (NVM) rises:
New memories such as ReRAM, MRAM, and PCM have analog computing capabilities and are naturally adapted to the storage and computing integration architecture. For example, the resistance state of ReRAM can directly participate in matrix operations.
Storage-class memory (SCM) popularization:
SCM technologies such as Intel Optane and Samsung Z-NAND have been mass-produced, providing PIM with high-performance, low-latency storage media.
4. Edge computing and IoT scenarios: energy efficiency revolution
The computing power dilemma of end-side devices:
Devices such as autonomous driving, AR/VR need to process massive amounts of data locally (such as 8K video streams). Storage and computing integration can reduce power consumption by 70% and extend battery life by 2-3 times.
Real-time requirements:
Predictive maintenance in industrial IoT needs to respond within microseconds, and storage and computing integration reduces data processing latency from milliseconds to nanoseconds.
5. Software ecology and algorithm collaboration: application scenario expansion
Sparse algorithm optimization:
Sparse matrices account for more than 95% of neural networks, and storage and computing integration can skip zero-value calculations, improving efficiency by more than 10 times.
Programming model evolution:
PIM-oriented spatial computing paradigms (such as NDA and GenASM) are gradually maturing, and developers can call computing units in storage.
6. Policy and capital promotion: global technology competition upgrades
National strategic support:
The US CHIPS Act and the EU's European Processor Initiative both list storage and computing integration as key directions. China's "14th Five-Year Plan" clearly supports the development of storage and computing integrated chips.
Capital inflow:
In 2023, global PIM financing will exceed US$5 billion, and giants such as Samsung, SK Hynix, and TSMC will accelerate their layout, and start-ups such as Mythic and UPMEM will receive multiple rounds of financing.
7. Supply chain reconstruction: from vertical integration to open collaboration
Industry chain collaboration:
Memory manufacturers (Micron, Kioxia) and IP suppliers (Synopsys, Cadence) cooperate to develop PIM design tool chains.
Foundries (SMIC, UMC) launched 2.5D/3D packaging technology to support mass production of integrated storage and computing chips.
Summary: The integrated storage and computing technology market is driven by computing power demand, hardware innovation, and policy capital. The core competition will focus on process integration capabilities (such as 3D stacking), algorithm-hardware co-design, and ecological openness. Chinese companies need to overcome the shortcomings of memory media and EDA tools and accelerate the commercialization of AI and edge scenarios.
This report studies the global Computing in Memory Technology demand, key companies, and key regions.
This report is a detailed and comprehensive analysis of the world market for Computing in Memory Technology, and provides market size (US$ million) and Year-over-Year (YoY) growth, considering 2025 as the base year. This report explores demand trends and competition, as well as details the characteristics of Computing in Memory Technology that contribute to its increasing demand across many markets.
Highlights and key features of the study
Global Computing in Memory Technology total market, 2021-2032, (USD Million)
Global Computing in Memory Technology total market by region & country, CAGR, 2021-2032, (USD Million)
U.S. VS China: Computing in Memory Technology total market, key domestic companies, and share, (USD Million)
Global Computing in Memory Technology revenue by player, revenue and market share 2021-2026, (USD Million)
Global Computing in Memory Technology total market by Type, CAGR, 2021-2032, (USD Million)
Global Computing in Memory Technology total market by Application, CAGR, 2021-2032, (USD Million)
This report profiles major players in the global Computing in Memory Technology market based on the following parameters - company overview, revenue, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include Syntiant, Zhicun(Witmem) Technology, Reexen Technology, Graphcore, Mythic, Shanyi Semiconductor, AistarTek, Samsung, SK Hynix, Houmo Technology, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Stakeholders would have ease in decision-making through various strategy matrices used in analyzing the world Computing in Memory Technology market
Detailed Segmentation:
Each section contains quantitative market data including market by value (US$ Millions), by player, by regions, by Type, and by Application. Data is given for the years 2021-2032 by year with 2025 as the base year, 2026 as the estimate year, and 2027-2032 as the forecast year.
Global Computing in Memory Technology Market, By Region:
United States
China
Europe
Japan
South Korea
ASEAN
India
Rest of World
Global Computing in Memory Technology Market, Segmentation by Type:
Near-Memory Computing
In-memory Computing
Processing In Memory
Global Computing in Memory Technology Market, Segmentation by Application:
Small Computing Power
Big Computing Power
Companies Profiled:
Syntiant
Zhicun(Witmem) Technology
Reexen Technology
Graphcore
Mythic
Shanyi Semiconductor
AistarTek
Samsung
SK Hynix
Houmo Technology
Pinxin Technology
Yizhu Intelligent Technology
TensorChip
Key Questions Answered
1. How big is the global Computing in Memory Technology market?
2. What is the demand of the global Computing in Memory Technology market?
3. What is the year over year growth of the global Computing in Memory Technology market?
4. What is the total value of the global Computing in Memory Technology market?
5. Who are the Major Players in the global Computing in Memory Technology market?
6. What are the growth factors driving the market demand?
As a new computing architecture, storage-computing integration is considered to be a revolutionary technology with potential and has received great attention at home and abroad. The core is to fully integrate storage and computing, effectively overcome the bottleneck of the von Neumann architecture, and combine advanced packaging and new storage devices in the post-Moore era to achieve an order of magnitude improvement in computing energy efficiency.
According to the distance between storage and computing, the technical solutions of generalized storage-computing integration are divided into three categories, namely, Processing Near Memory (PNM), Processing ln Memory (PlM) and Computing in Memory (CIM). In-memory computing is storage-computing integration in a narrow sense.
Global key players of Computing in Memory Technology include Syntiant, Zhicun(Witmem) Technology, Reexen Technology, Graphcore and Mythic, etc. The top five players hold a share over 80%. North America is the largest market, has a share about 50%. In terms of product type, In-memory Computing is the largest segment, occupied for a share of about 88%, and in terms of application, Small Computing Power has a share about 90 percent.
Analysis of the market drivers of Processing-in-Memory (PIM) technology,
1. Explosive growth in computing power demand: the underlying pressure of AI and big data
Demand for AI training and reasoning:
The global AI chip market is expected to reach US$120 billion in 2025, of which 75% of computing power is consumed in data transfer (not computing itself).
Large-scale language models (such as GPT-5) have more than 10 trillion parameters, and processing-in-memory (PIM) can improve the efficiency of sparse matrix operations by 3-5 times.
Data center energy consumption crisis:
Global data center power consumption accounts for 1.5% of total power demand, and data transfer energy consumption accounts for 40% in traditional architectures. Processing-in-Memory (PIM) can reduce energy consumption by more than 50% by reducing the memory wall effect.
2. Moore's Law slows down: an inevitable choice for architectural innovation
Process bottleneck:
The cost of advanced processes (below 3nm) has soared, and the marginal benefits of increasing transistor density have diminished. Processing-in-Memory integrates computing units through 3D stacking processes (such as HBM3) to break through the limitations of planar processes.
Heterogeneous computing needs:
Scenarios such as AI and graphics processing require customized computing units. Storage and computing integration supports the collaborative design of the logic layer and the storage layer to improve the efficiency of dedicated accelerators.
3. New storage technologies mature: hardware foundation is ready
Non-volatile memory (NVM) rises:
New memories such as ReRAM, MRAM, and PCM have analog computing capabilities and are naturally adapted to the storage and computing integration architecture. For example, the resistance state of ReRAM can directly participate in matrix operations.
Storage-class memory (SCM) popularization:
SCM technologies such as Intel Optane and Samsung Z-NAND have been mass-produced, providing PIM with high-performance, low-latency storage media.
4. Edge computing and IoT scenarios: energy efficiency revolution
The computing power dilemma of end-side devices:
Devices such as autonomous driving, AR/VR need to process massive amounts of data locally (such as 8K video streams). Storage and computing integration can reduce power consumption by 70% and extend battery life by 2-3 times.
Real-time requirements:
Predictive maintenance in industrial IoT needs to respond within microseconds, and storage and computing integration reduces data processing latency from milliseconds to nanoseconds.
5. Software ecology and algorithm collaboration: application scenario expansion
Sparse algorithm optimization:
Sparse matrices account for more than 95% of neural networks, and storage and computing integration can skip zero-value calculations, improving efficiency by more than 10 times.
Programming model evolution:
PIM-oriented spatial computing paradigms (such as NDA and GenASM) are gradually maturing, and developers can call computing units in storage.
6. Policy and capital promotion: global technology competition upgrades
National strategic support:
The US CHIPS Act and the EU's European Processor Initiative both list storage and computing integration as key directions. China's "14th Five-Year Plan" clearly supports the development of storage and computing integrated chips.
Capital inflow:
In 2023, global PIM financing will exceed US$5 billion, and giants such as Samsung, SK Hynix, and TSMC will accelerate their layout, and start-ups such as Mythic and UPMEM will receive multiple rounds of financing.
7. Supply chain reconstruction: from vertical integration to open collaboration
Industry chain collaboration:
Memory manufacturers (Micron, Kioxia) and IP suppliers (Synopsys, Cadence) cooperate to develop PIM design tool chains.
Foundries (SMIC, UMC) launched 2.5D/3D packaging technology to support mass production of integrated storage and computing chips.
Summary: The integrated storage and computing technology market is driven by computing power demand, hardware innovation, and policy capital. The core competition will focus on process integration capabilities (such as 3D stacking), algorithm-hardware co-design, and ecological openness. Chinese companies need to overcome the shortcomings of memory media and EDA tools and accelerate the commercialization of AI and edge scenarios.
This report studies the global Computing in Memory Technology demand, key companies, and key regions.
This report is a detailed and comprehensive analysis of the world market for Computing in Memory Technology, and provides market size (US$ million) and Year-over-Year (YoY) growth, considering 2025 as the base year. This report explores demand trends and competition, as well as details the characteristics of Computing in Memory Technology that contribute to its increasing demand across many markets.
Highlights and key features of the study
Global Computing in Memory Technology total market, 2021-2032, (USD Million)
Global Computing in Memory Technology total market by region & country, CAGR, 2021-2032, (USD Million)
U.S. VS China: Computing in Memory Technology total market, key domestic companies, and share, (USD Million)
Global Computing in Memory Technology revenue by player, revenue and market share 2021-2026, (USD Million)
Global Computing in Memory Technology total market by Type, CAGR, 2021-2032, (USD Million)
Global Computing in Memory Technology total market by Application, CAGR, 2021-2032, (USD Million)
This report profiles major players in the global Computing in Memory Technology market based on the following parameters - company overview, revenue, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include Syntiant, Zhicun(Witmem) Technology, Reexen Technology, Graphcore, Mythic, Shanyi Semiconductor, AistarTek, Samsung, SK Hynix, Houmo Technology, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Stakeholders would have ease in decision-making through various strategy matrices used in analyzing the world Computing in Memory Technology market
Detailed Segmentation:
Each section contains quantitative market data including market by value (US$ Millions), by player, by regions, by Type, and by Application. Data is given for the years 2021-2032 by year with 2025 as the base year, 2026 as the estimate year, and 2027-2032 as the forecast year.
Global Computing in Memory Technology Market, By Region:
United States
China
Europe
Japan
South Korea
ASEAN
India
Rest of World
Global Computing in Memory Technology Market, Segmentation by Type:
Near-Memory Computing
In-memory Computing
Processing In Memory
Global Computing in Memory Technology Market, Segmentation by Application:
Small Computing Power
Big Computing Power
Companies Profiled:
Syntiant
Zhicun(Witmem) Technology
Reexen Technology
Graphcore
Mythic
Shanyi Semiconductor
AistarTek
Samsung
SK Hynix
Houmo Technology
Pinxin Technology
Yizhu Intelligent Technology
TensorChip
Key Questions Answered
1. How big is the global Computing in Memory Technology market?
2. What is the demand of the global Computing in Memory Technology market?
3. What is the year over year growth of the global Computing in Memory Technology market?
4. What is the total value of the global Computing in Memory Technology market?
5. Who are the Major Players in the global Computing in Memory Technology market?
6. What are the growth factors driving the market demand?
Table of Contents
121 Pages
- 1 Supply Summary
- 2 Demand Summary
- 3 World Computing in Memory Technology Companies Competitive Analysis
- 4 United States VS China VS Rest of World (by Headquarter Location)
- 5 Market Analysis by Type
- 6 Market Analysis by Application
- 7 Company Profiles
- 8 Industry Chain Analysis
- 9 Research Findings and Conclusion
- 10 Appendix
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