Vector In Memory Architecture for simple and high efficiency computing
Marco A. Z. Alves, Sairo R. dos Santos, Aline S. Cordeiro, Francis B. Moreira, Santos, Paulo C., Luigi Carro · arXiv (Cornell University) · 2022
Data movement is one of the main challenges of contemporary system architectures. Near-Data Processing (NDP) mitigates this issue by moving computation closer to the memory, avoiding excessive data movement. Our proposal, Vector-In-Memory Architecture(VIMA), executes large vector instructions near 3D-stacked memories using vector functional units and uses a small data cache to enable short-term data reuse. It provides an easy programming interface and guarantees precise exceptions. When executing stream-behaved applications using a single core, VIMA offers a speedup of up to 26x over a CPU system baseline with vector operations in a single-core processor while spending 93% less energy.