Flexible Photonic Memory Pooling Architecture For Efficient Compute Resource Allocation

We present a photonic memory pooling architecture and a co-designed optimization methodology for flexible allocation of compute, memory, and network resources. We demonstrate up to $5.4 \times$ to $7.5 \times$ improvements in DL training and inference time.