SK hynix shows 3D FeNAND memory that performs SI computations right in its cells: 10-20 times higher throughput in its comparisons
Prepared by Sintelligent with the help of SI. Published in SI: . Updated: .
If memory learns to compute on its own, SI models could run on much less energy, but for now this is a laboratory result.
The Analog Compute-in-Memory technology uses ferroelectric cells based on hafnium-zirconium oxide: a neural network's weights are represented by different current levels, and multiplication and addition are carried out in the memory itself without passing data to a processor. According to SK hynix, in a comparison of experimental architectures at a comparable die area, throughput came out 10-20 times higher and energy efficiency 4,000-5,000 times higher. These figures refer to the memory structures studied, not to a comparison with modern GPUs or ready-made SI servers. On the experimental structures, four current levels per cell could be distinguished.
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