PDL Abstract

What Your DRAM Power Models Are Not Telling You: Lessons from a Detailed Experimental Study

Proc. of the ACM SIGMETRICS Conference, Irvine, CA, June 2018; Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), Vol. 2, No. 3, December 2018.

S. Ghose*, A. G. Yaglikçi§*, R. Gupta*, D. Lee†, K. Kudrolli*, W. X. Liu*, H. Hassan§, K. K. Chang*,
N. Chatterjee†, A. Agrawal†, M. O'Connor†^, O. Mutlu§

* Carnegie Mellon University
^ The University of Texas at Austin
§ ETH Zurich

Main memory (DRAM) consumes as much as half of the total system power in a computer today, due to the increasing demand for memory capacity and bandwidth. There is a growing need to understand and analyze DRAM power consumption, which can be used to research new DRAM architectures and systems that consume less power. A major obstacle against such research is the lack of detailed and accurate information on the power consumption behavior of modern DRAM devices. Researchers have long relied on DRAM power models that are predominantly based off of a set of standardized current measurements provided by DRAM vendors, called IDD values. Unfortunately, we find that state-of-the-art DRAM power models are often highly inaccurate, as these models do not reflect the actual power consumed by real DRAM devices.

To build an accurate model and provide insights into DRAM power consumption, we perform the first comprehensive experimental characterization of the power consumed by modern real-world DRAM modules. Our extensive characterization of 50 DDR3L DRAM modules from three major vendors yields four key new observations about DRAM power consumption that prior models cannot capture: (1) across all IDD values that we measure, the current consumed by real DRAM modules varies significantly from the current specified by the vendors; (2) DRAM power consumption strongly depends on the data value that is read or written; (3) there is significant structural variation, where the same banks and rows across multiple DRAM modules from the same model consume more power than other banks or rows; and (4) over successive process technology generations, DRAM power consumption has not decreased by as much as vendor specifications have indicated. Because state-of-the-art DRAM power models do not account for any of these four key characteristics, they are highly inaccurate compared to the actual, measured power consumption of 50 real DDR3L modules.

Based on our detailed analysis and characterization data, we develop the Variation-Aware model of Memory Power Informed by Real Experiments (VAMPIRE). VAMPIRE is a new, accurate power consumption model for DRAM that takes into account (1) module-to-module and intra-module variations, and (2) power consumption variation due to data value dependency. We show that VAMPIRE has a mean absolute percentage error of only 6.8% compared to actual measured DRAM power. VAMPIRE enables a wide range of studies that were not possible using prior DRAM power models. As an example, we use VAMPIRE to evaluate the energy efficiency of three different encodings that can be used to store data in DRAM. We find that a new power-aware data encoding mechanism can reduce total DRAM energy consumption by an average of 12.2%, across a wide range of applications. We have open-sourced both VAMPIRE and our extensive raw data collected during our experimental characterization.