Computing in Memory Technology Market Share, Sales Volume, Price Analysis Report 2026

Global Info Research's report offers an in-depth look into the current and future trends in Computing in Memory Technology, making it an invaluable resource for businesses involved in the sector. This data will help companies make informed decisions on research and development, product design, and marketing strategies. It also provides insights into Computing in Memory Technology' cost structure, raw material sources, and production processes. Additionally, it offers an understanding of the regulations and policies that are likely to shape the future of the industry. In essence, our report can help you stay ahead of the curve and better capitalize on industry trends.

According to our (Global Info Research) latest study, the global Computing in Memory Technology market size was valued at US$ 661 million in 2025 and is forecast to a readjusted size of USD million by 2032 with a CAGR of % during review period.
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 US0 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 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 is a detailed and comprehensive analysis for global Computing in Memory Technology market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.

Our Computing in Memory Technology Market report is a comprehensive study of the current state of the industry. It provides a thorough overview of the market landscape, covering factors such as market size, competitive landscape, key market trends, and opportunities for future growth. It also pinpoints the key players in the market, their strategies, and offerings.

Request PDF Sample Copy of Report: (Including Full TOC, List of Tables & Figures, Chart)
https://www.globalinforesearch.com/reports/3388186/computing-in-memory-technology

The research report encompasses the prevailing trends embraced by major manufacturers in the Computing in Memory Technology Market, such as the adoption of innovative technologies, government investments in research and development, and a growing emphasis on sustainability. Moreover, our research team has furnished essential data to illuminate the manufacturer's role within the regional and global markets.

The research study includes profiles of leading companies operating in the Computing in Memory Technology Market:

The report is structured into chapters, with an introductory executive summary providing historical and estimated global market figures. This section also highlights the segments and reasons behind their progression or decline during the forecast period. Our insightful Computing in Memory Technology Market report incorporates Porter's five forces analysis and SWOT analysis to decipher the factors influencing consumer and supplier behavior.

Segmenting the Computing in Memory Technology Market by application, type, service, technology, and region, each chapter offers an in-depth exploration of market nuances. This segment-based analysis provides readers with a closer look at market opportunities and threats while considering the political dynamics that may impact the market. Additionally, the report scrutinizes evolving regulatory scenarios to make precise investment projections, assesses the risks for new entrants, and gauges the intensity of competitive rivalry.

Major players covered: Syntiant、 Zhicun(Witmem) Technology、 Reexen Technology、 Graphcore、 Mythic、 Shanyi Semiconductor、 AistarTek、 Samsung、 SK Hynix、 Houmo Technology、 Pinxin Technology、 Yizhu Intelligent Technology、 TensorChip
Computing in Memory Technology Market by Type: Near-Memory Computing、 In-memory Computing、 Processing In Memory
Computing in Memory Technology Market by Application: Small Computing Power、 Big Computing Power

Key Profits for Industry Members and Stakeholders:

1. The report includes a plethora of information such as market dynamics scenario and opportunities during the forecast period.
2. Which regulatory trends at corporate-level, business-level, and functional-level strategies.
3. Which are the End-User technologies being used to capture new revenue streams in the near future.
4. The competitive landscape comprises share of key players, new developments, and strategies in the last three years.
5. One can increase a thorough grasp of market dynamics by looking at prices as well as the actions of producers and users.
6 Comprehensive companies offering products, relevant financial information, recent developments, SWOT analysis, and strategies by these players.

The content of the study subjects, includes a total of 15 chapters:
Chapter 1, to describe Computing in Memory Technology product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top manufacturers of Computing in Memory Technology, with price, sales, revenue and global market share of Computing in Memory Technology from 2020 to 2025.
Chapter 3, the Computing in Memory Technology competitive situation, sales quantity, revenue and global market share of top manufacturers are analyzed emphatically by landscape contrast.
Chapter 4, the Computing in Memory Technology breakdown data are shown at the regional level, to show the sales quantity, consumption value and growth by regions, from 2020 to 2031.
Chapter 5 and 6, to segment the sales by Type and application, with sales market share and growth rate by type, application, from 2020 to 2031.
Chapter 7, 8, 9, 10 and 11, to break the sales data at the country level, with sales quantity, consumption value and market share for key countries in the world, from 2020 to 2024.and Computing in Memory Technology market forecast, by regions, type and application, with sales and revenue, from 2025 to 2031.
Chapter 12, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 13, the key raw materials and key suppliers, and industry chain of Computing in Memory Technology.
Chapter 14 and 15, to describe Computing in Memory Technology sales channel, distributors, customers, research findings and conclusion.

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