Near-data accelerators (NDAs) that are integrated with the main memory have the potential
for significant power and performance benefits. Fully realizing these benefits requires the
large available memory capacity to be shared between the host and NDAs in a way that
permits both regular memory access by some applications and accelerating others with an
NDA, avoids copying data, enables collaborative processing, and simultaneously offers high
performance for both host and NDA. We identify and solve new challenges in this context …