The global high bandwidth memory market size was valued at USD 1,641.10 million in 2022. It is projected to reach USD 12.765.62 million by 2031, growing at a CAGR of 25.60% during the forecast period (2023-2031).
A high-speed computer memory interface for 3D-stacked SDRAM is known as high bandwidth memory (HBM). It is typically used with network devices, supercomputers, and high-performance graphics accelerators. HBM was a brand-new memory interface first introduced in 2013 and utilized stacked SDRAM coupled to the processor through a silicon interposer. Metal layers connect the memory to the SoC on that interposer. The other die is flipped over and joined by tiny bumps to be compared to a big chip or a PCB inside the package. A common name for this is 2.5D integration. HBM provides a significantly higher bandwidth while consuming less power in a comparably smaller form factor by stacking up to 8 DRAM dies on the circuit and linking them by TSVs.
In the ten years after the HBM standard was first introduced, 2.5 generations reached the market.According to Synopsys, throughout that time, data creation, capture, copying, and consumption surged from 2 zettabytes in 2010 to 64.2 ZB in 2020. Synopsys anticipates that quantity will expand nearly three times to 181 ZB in 2025. HBM2 increased the capacity to 256 GB/s and the signaling rate to 2 Gbps in 2016. HBM2E entered the market two years later and eventually reached data rates of about 3.6 Gbps and 460 GB/s.
Higher memory bandwidth is and will continue to be a crucial facilitator of computing performance. Therefore, the need for performance is growing, as are the relentless bandwidth needs of advanced applications (source: Synopsys).Companies are deciding whether to adopt 40GbE to the server as an upgrade from 10GbE to satisfy this rising demand for high bandwidth. 40GbE demands more power and more expensive cables, but 25GbE offers a more cost-effective throughput. To balance cost/performance tradeoffs, 25GbE is becoming recognized as the superior next-generation Ethernet speed for connecting servers.
Due to the complexity of the product, HBM is a potent version of an ultra-bandwidth solution, but it is also a somewhat expensive one. HBM2 is pricey. GDDR5 is nearly three times as expensive as this, assuming a high yield and a USD 20 adjustment (source: AMD Inc.). While HBM outperforms GDDR in terms of high bandwidth and applicability, it also has some drawbacks in terms of cost, capacity, and application complexity. As a result, many graphic card makers are implementing GDDR and HBM in different application domains. HBM3 makes sense in systems with an interposer, such as a chipset-based design that already used a silicon interposer for that purpose, according to chipmakers, who have made this abundantly evident.
The growing desire and need for smaller, lighter, and higher-performing electronics, also known as the downsizing of electronics and components, is one of the current trends in the consumer electronics business. Rapid technological advancements have made it possible to buy products with various functions on a single platform. Memory chips need smaller and thinner form factors to save space and be more compact, which is another breakthrough that calls for downsized electrical components. Autonomous vehicles' highly integrated, high-speed applications make it clear that better electrical performance and less space use are required. High bandwidth memory plays a more significant role in creating advanced electronic systems due to these factors in the design of the final products.
Automobile electrification has advanced in recent years, along with the development of automated driving systems like ADAS, and various electronic gadgets have been added to cars. However, because components frequently have to fit into small spaces, they must be downsized and have larger bandwidths available. The memory chip can achieve smaller form factors without compromising its performance thanks to the vertical stacking technology used for HBM and the connection to the host system-on-chip using 2.5D interposer technology. For high computing needs, which are currently constrained by form factor restrictions, businesses are developing HBM technology.
| Study Period | 2019-2031 | CAGR | 25.60% |
| Historical Period | 2019-2021 | Forecast Period | 2023-2031 |
| Base Year | 2022 | Base Year Market Size | USD 1,641.10 Million |
| Forecast Year | 2031 | Forecast Year Market Size | USD 12.765.62 Million |
| Largest Market | North America | Fastest Growing Market | Asia Pacific |
North America Dominates the Global Market
The global high bandwidth memory market is bifurcated into four regions: North America, Europe, Asia-Pacific, and LAMEA.
North America is the major revenue contributor and is expected to grow at a CAGR of 24.80% during the forecast period. The rapid expansion of high-performance computing (HPC) applications, which need high-bandwidth memory solutions for quick data processing, is mostly to blame for the high adoption of HBM in North America. The expanding market for cloud computing, AI, and machine learning drives up HPC demand in North America. Additionally, the HPC industry benefits the American economy directly. The HPC sector generates a positive net trade balance. Regardless of which companies built the HPC systems, most of the microprocessors used in the world's top HPC machines were created in the United States. Microsoft, Amazon, and other significant tech firms also have their headquarters in the US.
Asia-Pacific is expected to grow at a CAGR of 25.60% during the forecast period. The cumulative growth of computing power is rising in Japan. From June 2019 to June 2021, there were 34 supercomputers, up from 29 according to TOP500. The HPC Asia 2020 program has emphasized the creation of HPC-specific systems, notably for social and scientific goals, even though HPC systems in Japan are typically deployed throughout data centers. This objective has been motivated by considering the most significant problems, such as the need to sustain clean energy, healthcare, aging, and natural issues like earthquakes and climate change. All three of China's exascale systems are designed around locally produced CPUs.
The European Union announced the installation of cutting-edge safety features in all new cars beginning in mid-2022 to lower the number of traffic deaths. Companies will experience an increase in the need for obligatory elements for cars to be fitted with an autonomous driving system for all incoming vehicles by 2025 due to the growing demand for stricter regulatory norms by the European Union for safety and environmental reasons. Additionally, it is anticipated that the market for HBM will grow with newer deals and investments. For example, in June 2020, Mipsology, a European company specializing in AI and machine learning software, agreed to include its Zebra neural network accelerating software in the most recent version of Xilinx's Alveo U50 data center accelerator card.
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The global high bandwidth memory market is segmented by application.
Based on application, the global high bandwidth memory market is bifurcated into servers, networking, consumer, automotive, and others.
The server segment is the highest contributor to the market and is estimated to grow at a CAGR of 25.30% during the forecast period. A considerable demand for reduced latency exists right now for servers, which are high-end equipment. Memory walls are a typical problem that servers encounter. Data movement between the processor and the DRAM causes higher power consumption and latency problems, as indicated by the memory wall. By using faster DRAM, such as HBM, the memory wall problem can be solved. The foundation of HBM technology is putting memory and logic closer together to increase speed and assist in breaking the memory wall. Data processing speed among servers in data centers is a significant concern due to the proliferation of data. A further factor in adopting High Bandwidth Memory is the expansion of data centers.
The rapid usage of 3D characterizes the semiconductor industry stacked high bandwidth memory based on a through silicon via (TSV) and fine pitch interposer technology, which addresses the issues of high density and high bandwidth in networking. The creation and subsequent implementation of HBM technology in networking have been made possible by the exponential expansion of network traffic and the restrictions on the bandwidth availability of DDR memory. The stacking technology most suited for networking is one of the many features of HBM technology that is still evolving. It is possible to identify stakeholders along the value chain to launch new solutions that address networking's performance constraints because of the HBM technology's numerous applications and necessities.
The study segment's need for HBM is driven by the advanced graphics requirements of modern consumer devices. HBM is being made possible by the expanding use of cutting-edge technologies such as artificial intelligence and machine learning, as well as its incorporation with consumer devices. Developers of HBM should pay close attention to consumer video cards. Increased graphics card capacity and adoption of HBM technology are priorities for stakeholders like AMD and Nvidia. To improve its gaming products, AMD lavishly invested in HBM technology for years before integrating it with its graphics card as early as June 2015 to its Radeon R9 Fury X. In terms of rising demand and utilization, it is predicted that the HBM market will advance significantly over the projection year.
Due to the expansion of ADAS integration and self-driving cars, among other factors, high bandwidth memory applications are extending throughout the automobile industry. High-performance memory has become more widely used due to developments in the automobile industry, fostering the expansion of high-bandwidth memory. With 2.5D technology, HBM has evolved from regular DRAM to a higher level, enabling it to travel closer to the processor while consuming less power and experiencing less RC latency. In order to process and analyze the environment, autonomous driving uses massive data sets, a rapidly growing area of the automobile industry. To prevent mishaps and impending tragedies, data processing is carried out at a very fast rate.
