  Data-intensive applications like distributed AI-training may require
multi-terabytes memory capacity with multi-terabits bandwidth. We directly
attach the memory to the ethernet controller with some programable logic to
design an efficient hardware "template" for Memory pooling and in-memory /
in-network computing. We built an FPGA prototype of the NetDAM, andwe
demonstrate MPI-Allreduce communication case, the NetDAM can be used as a
software and hardware friendly programmable architeture with high performance
alternative for RDMA.

Distributed, Parallel, and Cluster Computing