SK hynix-TetraMem collaboration featured on Tom’s Hardware
Read how Tom’s Hardware spotlights TetraMem’s joint work with SK
Read how Tom’s Hardware spotlights TetraMem’s joint work with SK
Our joint research paper with the SK Hynix, “A Memristor-based In-Memory Computing SoC with Efficient Depthwise Convolution,” has been accepted and published online in Advanced Intelligent Systems https://advanced.onlinelibrary.wiley.com/doi/10.1002/aisy.202501225
TetraMem Completes MLX200 Silicon Validation. TetraMem’s MLX200 is the first multi-level RRAM analogue in-memory computing SoC on 22nm silicon, delivering energy-efficient AI inference for edge, IoT, and wearables.
TetraMem and researchers from the University of Southern California and the University of Massachusetts Amherst demonstrated RRAM (memristor) devices capable of reliable operation at temperatures up to 700°C. Science article “High-temperature memristors enabled by interfacial engineering.” https://www.science.org/doi/10.1126/science.aeb9934
TetraMem will introduce its multi-level RRAM cell for in-memory computing. The talk will explain how TetraMem uses Multi-level RRAM to accelerate neural network inference applications.
EE Times’ 25th revision of the Silicon 100, our annual
We’re excited to share news that our CEO, Dr. Glenn
https://www.prnewswire.com/news-releases/tetramem-inc-and-sk-hynix-announce-research-partnership-302307644.html
In another milestone, TetraMem’s VP of IC Design, Wenbo Yin,