Closed-Form Optimal Weight Splitting for Matrix-Vector Multiply on Noisy In-Memory Accelerators

Analog in-memory computing performs the matrix-vector multiplications of neural networks directly inside the memory array, which saves time and energy. But each memory cell stores only a few levels and is noisy, so one cell cannot hold a weight precisely. The standard fix is to split each weight acr