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Revolutionizing AI With High-Bandwidth Memory (TechArena Infographic)
Lam Blog Staff
Sep 12, 2024
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By 2027, the demand for high-bandwidth memory (HBM) is expected to rise substantially due to its capability to deliver better latency and meet the efficiency and density requirements of AI applications.  

Lam Research offers a broad array of industry-leading tools and solutions designed to scale high-bandwidth memory (HBM) to satisfy these AI requirements. Discover details in this infographic from TechArena. 

AI is driving an acceleration of compute demands fueled by the proliferation of large language models across industry use cases. Memory capacity of up to 8x the size of training model parameters reveals the need for low latency, high-capacity memory that scales efficiently with compute.1 This requirement comes as traditional semiconductor technology pushes against the laws of physics with the slowing of Moore’s Law. Advanced 2.5D and 3D packaging has emerged as critical for further advancement of semiconductor speed with High Bandwidth Memory (HBM) the leading solution leveraging this powerful capability. HBM is connected directly atop compute to deliver the improved latency, efficiency and density that AI applications demand. $200B in CapEx investment in Data Center by 2028. $15.7T contributed by AI to the global economy by 2030. $1 trillion total semiconductor revenue by 2030. 20% growth in DRAM equipment sales in 2025 alone. High-bandwidth memory bit demand will grow eightfold, from 123 million GBs in 2022 to 972 million GBs in 2027, driven by the need for high-performance memory in general AI and generative AI models. By 2027, HBM bit consumption will grow to 1.6% of total DRAM consumption, up from 0.5% in 2022. Lam Research Advanced Packaging Wide range of essential solutions and industry-leading tools help scale HBM for the future of AI, including: Syndion Silicon Etch, Vector CVD Films Dep and Interdie Gapfill, and SABRE/SABRE 3D Electroplating.

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