Energy-Efficient Streaming Using Non-volatile Memory

The disk and the DRAM in a typical mobile system consume a significant fraction (up to 30%) of the total system energy. To save on storage energy, the DRAM should be small and the disk should be spun down for long periods of time. We show that this can be achieved for predominantly streaming workloads by connecting the disk to the DRAM via a large non-volatile memory (NVM). We refer to this as the NVM-based architecture (NVMBA); the conventional architecture with only a DRAM and a disk is referred to as DRAMBA. The NVM in the NVMBA acts as a traffic reshaper from the disk to the DRAM. The total system costs are balanced, since the cost increase due to adding the NVM is compensated by the decrease in DRAM cost. We analyze the energy saving of NVMBA, with NAND flash memory serving as NVM, relative to DRAMBA with respect to (1) the streaming demand, (2) the disk form factor, (3) the best-effort provision, and (4) the stream location on the disk. We present a worst-case analysis of the reliability of the disk drive and the flash memory, and show that a small flash capacity is sufficient to operate the system over a year at negligible cost. Disk lifetime is superior to flash, so that is of no concern

A Composable Worst Case Latency Analysis for Multi-Rank DRAM Devices under Open Row Policy

The final publication is available at Springer via http://dx.doi.org/10.1007/s11241-016-9253-4As multi-core systems are becoming more popular in real-time embedded systems, strict timing requirements for accessing shared resources must be met. In particular, a detailed latency analysis for Double Data Rate Dynamic RAM (DDR DRAM) is highly desirable. Several researchers have proposed predictable memory controllers to provide guaranteed memory access latency. However, the performance of such controllers sharply decreases as DDR devices become faster and the width of memory buses is increased. High-performance Commercial-Off-The-Shelf (COTS) memory controllers in general-purpose systems employ open row policy to improve average case access latencies and memory throughput, but the use of such policy is not compatible with existing real-time controllers. In this article, we present a new memory controller design together with a novel, composable worst case analysis for DDR DRAM that provides improved latency bounds compared to existing works by explicitly modeling the DRAM state. In particular, our approach scales better with increasing memory speed by predictably taking advantage of shorter latency for access to open DRAM rows. Furthermore, it can be applied to multi-rank devices, which allow for increased access parallelism. We evaluate our approach based on worst case analysis bounds and simulation results, using both synthetic tasks and a set of realistic benchmarks. In particular, benchmark evaluations show up to 45% improvement in worst case task execution time compared to a competing predictable memory controller for a system with 16 requestors and one rank.NSERC DG || 402369-2011 CMC Microsystem

An analyzable memory controller for hard real-time CMPs

Multicore processors (CMPs) represent a good solution to provide the performance required by current and future hard real-time systems. However, it is difficult to compute a tight WCET estimation for CMPs due to interferences that tasks suffer when accessing shared hardware resources.We propose an analyzable JEDEC-compliant DDRx SDRAM memory controller (AMC) for hard real-time CMPs, that reduces the impact of memory interferences caused by other tasks on WCET estimation, providing a predictable memory access time and allowing the computation of tight WCET estimations.Peer ReviewedPostprint (published version

An extensible framework for multicore response time analysis

In this paper, we introduce a multicore response time analysis (MRTA) framework, which decouples response time analysis from a reliance on context independent WCET values. Instead, the analysis formulates response times directly from the demands placed on different hardware resources. The MRTA framework is extensible to different multicore architectures, with a variety of arbitration policies for the common interconnects, and different types and arrangements of local memory. We instantiate the framework for single level local data and instruction memories (cache or scratchpads), for a variety of memory bus arbitration policies, including: Round-Robin, FIFO, Fixed-Priority, Processor-Priority, and TDMA, and account for DRAM refreshes. The MRTA framework provides a general approach to timing verification for multicore systems that is parametric in the hardware configuration and so can be used at the architectural design stage to compare the guaranteed levels of real-time performance that can be obtained with different hardware configurations. We use the framework in this way to evaluate the performance of multicore systems with a variety of different architectural components and policies. These results are then used to compose a predictable architecture, which is compared against a reference architecture designed for good average-case behaviour. This comparison shows that the predictable architecture has substantially better guaranteed real-time performance, with the precision of the analysis verified using cycle-accurate simulation