In Depth
High Bandwidth Memory (HBM) is a specialized memory technology that stacks multiple layers of DRAM vertically and connects them to the processor through a wide interface called a silicon interposer. This 3D stacking provides dramatically higher bandwidth than traditional memory while consuming less power and physical space.
HBM is essential for AI accelerators because large model training and inference are fundamentally memory-bandwidth-limited operations. The massive matrices involved in transformer computations require moving enormous amounts of data between memory and compute cores. NVIDIA's H100 GPU uses HBM3 providing over 3 TB/s of bandwidth, and the B200 uses HBM3e with even higher bandwidth. Without HBM, modern AI hardware simply could not achieve practical performance levels.
HBM supply and pricing significantly impact the AI hardware market. SK Hynix, Samsung, and Micron are the primary manufacturers, and demand from AI chip makers has consistently strained supply. HBM availability is a key factor in GPU production timelines and pricing, which in turn affects AI training costs and model development timelines across the industry.