AI/ML training capabilities are growing at a rate of 10X per year driving rapid improvements in every aspect of computing hardware and software. HBM2E memory is the ideal solution for the high bandwidth requirements of AI/ML training, but entails additional design considerations given its 2.5D architecture. Designers can realize the full benefits of HBM2E memory with the silicon-proven memory subsystem solution from Rambus.

Download this white paper to:

  • Evolution of HBM standard to HBM2E
  • Design challenges and considerations
  • Features of Rambus HBM2E memory subsystem

Download the Rambus HBM2E Interface white paper