NDA: Near-DRAM acceleration architecture leveraging commodity DRAM devices and standard memory modules

TLDR: This paper proposes near-DRAM acceleration (NDA) architectures, which process data using accelerators 3D-stacked on DRAM devices comprising off-chip main memory modules, substantially reducing energy consumption and improving performance.

Abstract: Energy consumed for transferring data across the processor memory hierarchy constitutes a large fraction of total system energy consumption, and this fraction has steadily increased with technology scaling. In this paper, we propose near-DRAM acceleration (NDA) architectures, which process data using accelerators 3D-stacked on DRAM devices comprising off-chip main memory modules. NDA transfers most data through high-bandwidth and low-energy 3D interconnects between accelerators and DRAM devices instead of low-bandwidth and high-energy off-chip interconnects between a processor and DRAM devices, substantially reducing energy consumption and improving performance. Unlike previous near-memory processing architectures, NDA is built upon commodity DRAM devices; apart from inserting through-silicon vias (TSVs) to 3D-interconnect DRAM devices and accelerators, NDA requires minimal changes to the commodity DRAM device and standard memory module architectures. This allows NDA to be more easily adopted in both existing and emerging systems. Our experiments demonstrate that, on average, our NDA-based system consumes 46% (68%) lower (data transfer) energy at 1.67× higher performance than a system that integrates the same accelerator logic within the processor itself.