Dynamic Command Scheduling for Real-Time Memory Controllers

Memory controller design is challenging as real-time embedded systems feature an increasing diversity of real-time and non-real-time applications with variable transaction sizes. To satisfy the requirements of the applications, tight bounds on the worst-case execution time (WCET) of memory transactions must be provided to real-time applications, while the lowest possible average execution time must be given to the rest. Existing real-time memory controllers cannot efficiently achieve this goal as they either bound the WCET by sacrificing the average execution time, or are not scalable to directly support variable transaction sizes, or both. In this paper, we propose to use dynamic command scheduling, which is capable of efficiently dealing with transactions with variable sizes. The three main contributions of this paper are: 1) a back-end architecture for a real-time memory controller with a dynamic command scheduling algorithm, 2) a formalization of the timings of the memory transactions for the proposed architecture and algorithm, and 3) two techniques to bound the WCET of transactions with both fixed and variable sizes, respectively. We experimentally evaluate the proposed memory controller and compare both the worst-case and average-case execution times of transactions to a state-of-the-art semi-static approach. The results demonstrate that dynamic command scheduling outperforms the semi-static approach by 33.4% in the average case and performs at least equally well in the worst case. We also show the WCET is tight for transactions with fixed and variable sizes, respectively

Modeling and Verification of Dynamic Command Scheduling for Real-Time Memory Controllers

Real-Time and Embedded Technology and Applications Symposium (RTAS 2016). 11 to 14, Apr, 2016, Track 3: Embedded Systems Design for Real-Time Applications. Vienna, Austria.In modern multi-core systems with multiple real-time (RT) applications, memory traffic accessing the shared SDRAM is increasingly diverse, e.g., transactions have variable sizes. RT memory controllers with dynamic command scheduling can efficiently address the diversity by issuing appropriate commands subject to the SDRAM timing constraints. However, the scheduling dependencies between commands make it challenging to derive tight bounds for the worst-case response time (WCRT) and the worst-case bandwidth (WCBW) of a memory controller. Existing modeling and analysis techniques either do not provide tight WCRT and WCBW bounds for diverse memory traffic with variable transaction sizes or are difficult to adapt to different RT memory controllers. This paper models a memory controller using Timed Automata (TA), where model checking is applied for analysis. Our TA model is modular and accurately captures the behavior of a RT memory controller with dynamic command scheduling. We obtain WCRT and WCBW bounds, which are validated by simulating the worst-case transaction traces obtained by model checking with a cycle-accurate model of the memory controller. Our method outperforms three state-of-the-art analysis techniques. We reduce WCRT bound by up to 20%, while the average improvement is 7.7%, and increase the WCBW bound by up to 25% with an average improvement of 13.6%. In addition, our modeling is generic enough to extend to memory controllers with different mechanisms.info:eu-repo/semantics/publishedVersio

Modeling and Verification of Dynamic Command Scheduling for Real-Time Memory Controllers

In modern multi-core systems with multiple real-time (RT) applications, memory traffic accessing the shared SDRAM is increasingly diverse, e.g., transactions have variable sizes. RT memory controllers with dynamic command scheduling can efficiently address the diversity by issuing appropriate commands subject to the SDRAM timing constraints. However, the scheduling dependencies between commands make it challenging to derive tight bounds for the worst-case response time (WCRT) and the worst-case bandwidth (WCBW) of a memory controller. Existing modeling and analysis techniques either do not provide tight WCRT and WCBW bounds for diverse memory traffic with variable transaction sizes or are difficult to adapt to different RT memory controllers. This paper models a memory controller using Timed Automata (TA), where model checking is applied for analysis. Our TA model is modular and accurately captures the behavior of a RT memory controller with dynamic command scheduling. We obtain WCRT and WCBW bounds, which are validated by simulating the worst- case transaction traces obtained by model checking with a cycle-accurate model of the memory controller. Our method outperforms three state-of-the-art analysis techniques. We reduce WCRT bound by up to 20%, while the average improvement is 7.7%, and increase the WCBW bound by up to 25% with an average improvement of 13.6%. In addition, our modeling is generic enough to extend to memory controllers with different mechanisms

Parallelism-Aware Memory Interference Delay Analysis for COTS Multicore Systems

In modern Commercial Off-The-Shelf (COTS) multicore systems, each core can generate many parallel memory requests at a time. The processing of these parallel requests in the DRAM controller greatly affects the memory interference delay experienced by running tasks on the platform. In this paper, we model a modern COTS multicore system which has a nonblocking last-level cache (LLC) and a DRAM controller that prioritizes reads over writes. To minimize interference, we focus on LLC and DRAM bank partitioned systems. Based on the model, we propose an analysis that computes a safe upper bound for the worst-case memory interference delay. We validated our analysis on a real COTS multicore platform with a set of carefully designed synthetic benchmarks as well as SPEC2006 benchmarks. Evaluation results show that our analysis is more accurately capture the worst-case memory interference delay and provides safer upper bounds compared to a recently proposed analysis which significantly under-estimate the delay.Comment: Technical Repor

The Octopus switch

This chapter1 discusses the interconnection architecture of the Mobile Digital Companion. The approach to build a low-power handheld multimedia computer presented here is to have autonomous, reconfigurable modules such as network, video and audio devices, interconnected by a switch rather than by a bus, and to offload as much as work as possible from the CPU to programmable modules placed in the data streams. Thus, communication between components is not broadcast over a bus but delivered exactly where it is needed, work is carried out where the data passes through, bypassing the memory. The amount of buffering is minimised, and if it is required at all, it is placed right on the data path, where it is needed. A reconfigurable internal communication network switch called Octopus exploits locality of reference and eliminates wasteful data copies. The switch is implemented as a simplified ATM switch and provides Quality of Service guarantees and enough bandwidth for multimedia applications. We have built a testbed of the architecture, of which we will present performance and energy consumption characteristics

Mode-Controlled Data-Flow Modeling of Real-Time Memory Controllers

Accepted in 13th IEEE Symposium on Embedded Systems for Real-Time Multimedia (ESTIMedia 2015), Amsterdam, Netherlands.SDRAM is a shared resource in modern multi-core platforms executing multiple real-time (RT) streaming applications. It is crucial to analyze the minimum guaranteed SDRAM bandwidth to ensure that the requirements of the RT streaming applications are always satisfied. However, deriving the worst-case bandwidth (WCBW) is challenging because of the diverse memory traffic with variable transaction sizes. In fact, existing RT memory controllers either do not efficiently support variable transaction sizes or do not provide an analysis to tightly bound WCBW in their presence. We propose a new mode-controlled data-flow (MCDF) model to capture the command scheduling dependencies of memory transactions with variable sizes. The WCBW can be obtained by employing an existing tool to automatically analyze our MCDF model rather than using existing static analysis techniques, which in contrast to our model are hard to extend to cover different RT memory controllers. Moreover, the MCDF analysis can exploit static information about known transaction sequences provided by the applications or by the memory arbiter. Experimental results show that 77% improvement of WCBW can be achieved compared to the case without known transaction sequences. In addition, the results demonstrate that the proposed MCDF model outperforms state-of-the-art analysis approaches and improves the WCBW by 22% without known transaction sequences