You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

27 lines
2.9 KiB

author={A. Farmahini-Farahani and J. Ho Ahn and K. Morrow and N. Sung Kim},
journal={IEEE Computer Architecture Letters},
title={DRAMA: An Architecture for Accelerated Processing Near Memory},
abstract={Improving energy efficiency is crucial for both mobile and high-performance computing systems while a large fraction of total energy is consumed to transfer data between storage and processing units. Thus, reducing data transfers across the memory hierarchy of a processor (i.e., off-chip memory, on-chip caches, and register file) can greatly improve the energy efficiency. To this end, we propose an architecture, DRAMA, that 3D-stacks coarse-grain reconfigurable accelerators (CGRAs) atop off-chip DRAM devices. DRAMA does not require changes to the DRAM device architecture, apart from through-silicon vias (TSVs) that connect the DRAM device's internal I/O bus to the CGRA layer. We demonstrate that DRAMA can reduce the energy consumption to transfer data across the memory hierarchy by 66-95 percent while achieving speedups of up to 18× over a commodity processor.},
keywords={DRAM chips;energy conservation;storage management;3D-stacks coarse-grain reconfigurable accelerators;DRAM devices;DRAMA architecture;TSV;accelerated near memory processing;data transfers;dynamic random access memory;energy consumption reduction;energy efficiency;high-performance computing systems;memory hierarchy;mobile computing systems;processing units;storage units;through-silicon vias;total energy fraction;Acceleration;Arrays;Kernel;Memory management;Random access memory;Registers;Near memory processing, DRAM, 3D-stacking, energy-efficient computing, accelerator},
author={R. Balasubramonian and J. Chang and T. Manning and J. H. Moreno and R. Murphy and R. Nair and S. Swanson},
journal={IEEE Micro},
title={Near-Data Processing: Insights from a MICRO-46 Workshop},
abstract={The cost of data movement in big-data systems motivates careful examination of near-data processing (NDP) frameworks. The concept of NDP was actively researched in the 1990s, but gained little commercial traction. After a decade-long dormancy, interest in this topic has spiked. A workshop on NDP was organized at MICRO-46 and was well attended. Given the interest, the organizers and keynote speakers have attempted to capture the key insights from the workshop into an article that can be widely disseminated. This article describes the many reasons why NDP is compelling today and identifies key upcoming challenges in realizing the potential of NDP.},
keywords={Bandwidth allocation;Big data;Computational modeling;Computer architecture;Costs;Distributed databases;History;big data;data movement;history of computing;near-data processing},