DRAM memory is a major resource shared among cores in a chip multiprocessor (CMP) system. Memory requests from different threads can interfere with each other. Existing memory access scheduling techniques try to optimize the overall data throughput obtained from the DRAM and thus do not take into account inter-thread interference. Therefore, different threads running together on the same chip can experience extremely different memory system performance: one thread can experience a severe slowdown or starvation while another is unfairly prioritized by the memory scheduler.This paper proposes a new memory access scheduler, called the Stall-Time Fair Memory scheduler (STFM), that provides quality of service to different threads sharing the DRAM memory system. The goal of the proposed scheduler is to "equalize" the DRAM-related slowdown experienced by each thread due to interference from other threads, without hurting overall system performance. As such, STFM takes into account inherent memory characteristics of each thread and does not unfairly penalize threads that use the DRAM system without interfering with other threads.We show that STFM significantly reduces the unfairness in the DRAM system while also improving system throughput (i.e., weighted speedup of threads) on a wide variety of workloads and systems. For example, averaged over 32 different workloads running on an 8-core CMP, the ratio between the highest DRAM-related slowdown and the lowest DRAM-related slowdown reduces from 5.26X to 1.4X, while the average system throughput improves by 7.6%. We qualitatively and quantitatively compare STFM to one new and three previouslyproposed memory access scheduling algorithms, including network fair queueing. Our results show that STFM provides the best fairness, system throughput, and scalability.
Emerging three-dimensional (3D) integration technology allows for the direct placement of DRAM on top of a microprocessor, significantly reducing the wire-delay between the two and thereby alleviating memory latency and bandwidth constraints. However, the increase in power density of 3D technology leads to elevated on-chip temperature, which results in an exponential rise in charge leakage of DRAM. Consequently, the refresh frequency of 3D die-stacked DRAM needs to be doubled (or more) to retain data at the expense of additional power overhead. In this work, we investigate using Phase-change Random Access Memory (PRAM) as a promising candidate to achieve scalable, low power and thermal friendly memory system architecture in the upcoming 3D-stacking technology era. Using analytical model, circuit-and architectural-level simulations that capture both physical and electrical characteristics of PRAM, we show that the higher temperature of 3D chips is beneficial to PRAM power savings due to its unique, heat-driven programming mechanisms. Moreover, we show that the Through Silicon Vias (TSVs) ubiquitously used in 3D implementations contribute further PRAM power savings due to their substantially lower resistance to the high PRAM programming current.To effectively integrate PRAM into a conventional memory hierarchy, we propose architecture and OS support to address its write latency and reliability disadvantages. We present a hybrid PRAM/DRAM memory architecture and exploit an OSlevel paging scheme to improve PRAM write performance and lifetime. Moreover, we leverage the error-correcting capability of strong ECC codes to expand PRAM lifespan and use wearout aware OS page allocation to minimize ECC performance overhead. Our experimental results show that compared to diestacked planar DRAM, our design reduces the overall power consumption of the memory system by 54% with 6% performance degradation, consequently alleviating the thermal constraint of 3D chips by up to 4.25°C and achieving a speedup of up to 1.1X. We also show that the lifetime can be improved by a factor of 114X using the proposed endurance optimization schemes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.