TetraMem is excited and honored to be named Semiconductor Review’s Top In-Memory Computing Solution for 2023, and for our CEO, Dr. Glenn Ge to have been interviewed for the cover of the current edition. Please read the full article at the link!
https://www.semiconductorreview.com/magazines/December2023/In_Memory_Computing/
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
