Needless to say, the demand for Dynamic Random-Access Memory (DRAM) has increased exponentially. This growth is largely due to the explosive expansion of artificial intelligence (AI) data centers. This critical semiconductor memory element drives the revolution in GPUs and other accelerators. It has an increasing importance to augmenting AI tools. The DRAM industry today is enjoying an unprecedented boom. This rapid expansion is creating serious supply shortages that are beginning to severely affect numerous industries that rely on semiconductor memory technology.
The AI bubble and DRAM are caught in a typical boom and bust cycle. This arcane phenomenon is perhaps best known from the semiconductor industry. Sensitivity to DRAM prices High demand is causing DRAM prices to surge. Making sure everyone has what they need to meet this new surge is a daunting task. The industry is experiencing the greatest challenges it has ever faced right now. A singular emphasis on fulfilling AI-related needs is siphoning supply from all equally critical applications.
Understanding DRAM Structure and Functionality
Because DRAM is architecturally designed in a tower-like structure, with its components vertically stacked to increase speed and efficiency. Each stack consists of multiple memory dies. The base die handles all the data movement between the non-volatile memory stacks and the processor itself. The overall height of these DRAM towers is around just 750 micrometers, small in stature but mighty in capabilities.
In addition to representational features, the high-bandwidth memory (HBM) chips are DRAM technology’s most consequential application. These chips clamp tightly against both faces of the processor. This configuration increases data throughput paving the way for the most demanding AI workloads. For example, DRAM chips get clustered together with GPUs on the same interconnected chips. Together, this pairing reduces the time it takes to move data and increases overall processing efficiency.
The HBM4 specification as it stands today already allows for up to 16 DRAM dies stacked on top of one another. Twelve dies are used today for most DRAM chips. With each advancement in technology, the possibilities for memory stacking grow.
The Intersection of AI Demand and Supply Chain Challenges
As AI technology is quickly developing and moving into new infrastructure, this continuing expansion has collided with TSMC’s innovation enabling the classic boom and bust cycle of the DRAM business. This convergence has created historic demand, widespread disruption of supply chains, and unprecedented price increases. The more businesses and organizations fight for the limited memory components AI infrastructure needs to run, the higher the stakes and the supply shortages become.
As the global leader in the DRAM market, Samsung is in position to continue rising to the moment with DRAM-related programs and investments. The firm expects to begin manufacturing at a new plant in Pyeongtaek, South Korea, in 2028. This expansion seeks to increase production and meet the increasing demand from the fast-expanding AI sector.
“Relief will come from a combination of incremental capacity expansions by existing DRAM leaders, yield improvements in [advanced packaging], and a broader diversification of supply chains,” – Shawn DuBravac
Industry leaders agree that cutting-edge advanced manufacturing processes will be key to overcoming supply chain challenges. Expanding maker spaces is one of the primary strategies.
Price Trends and Future Outlook
Yes, prices are indeed currently soaring, but history tells us that cuts are always slow and reluctant in coming after inflationary episodes. So look for a slow bleed, not a cliff. For example, industry analyst Mina Kim recently highlighted the declining impact of the construction spending stimulus. As most economists will tell you, prices usually fall more slowly and less enthusiastically than they increase. DRAM today isn’t immune to this broad reality, particularly with the endless need for compute.
The ongoing, strong demand for DRAM in AI workloads makes the market picture more complicated. As enterprises continue to pour billions of dollars into AI capabilities, making sure they have enough memory will be the key to their success. The continued supply chain struggles require the need for more strategic planning and innovation to be found within the industry.
“There are two ways to address supply issues with DRAM: with innovation or with building more fabs,” – Mina Kim