Performance gains in memory have traditionally been obtained by increasing memory bus widths and speeds. The diminishing returns of such techniques have led to the proposal of an alternate architecture, the fully-buffered DIMM. This new standard replaces the conventional memory bus with a narrow, high-speed interface between the memory controller and the DIMMs. This paper examines how traditional DDRx based memory controller policies for scheduling and row buffer management perform on a fully-buffered DIMM memory architecture. The split-bus architecture used by FBDIMM systems results in an average improvement of 7% in latency and 10% in bandwidth at higher utilizations. On the other hand, at lower utilizations, the increased cost of serialization resulted in a degradation in latency and bandwidth of 25% and 10% respectively. The split-bus architecture also makes the system performance sensitive to the ratio of read and write traffic in the workload. In larger configurations, we found that the FBDIMM system performance was more sensitive to usage of the FBDIMM links than to DRAM bank availability. In general, FBDIMM performance is similar to that of DDRx systems, and provides better performance characteristics at higher utilization, making it a relatively inexpensive mechanism for scaling capacity at higher bandwidth requirements. The mechanism is also largely insensitive to scheduling policies, provided certain ground rules are obeyed

The development of energy-conscious embedded and/or mobile systems exposes a trade-off between energy consumption and system performance. Recent microprocessors have incorporated dynamic voltage scaling as a tool that system software can use to explore this trade-off. Developing appropriate heuristics to control this feature is a non-trivial venture; as has been shown in the past, voltage-scaling heuristics that closely track perceived performance requirements do not save much energy, while those that save the most energy tend to do so at the expense of performance resulting in poor response time, for example. We note that the task of dynamically scaling processor speed and voltage to meet changing performance requirements resembles a classical control-systems problem, and so we apply a bit of control theory to the task in order to define a new voltage-scaling algorithm. We find that, using our nqPID (not quite PID) algorithm, one can improve upon the current best-of-class heuristic Pering's AVGN algorithm, based on Govil's AGED AVERAGES algorithm and Weiser's PAST algorithm in both energy consumption and performance. The study is execution-based, not-trace-based; the voltage-scaling heuristics were integrated into an embedded operating system running on a Motorola M-CORE processor model. The applications studied are all members of the MediaBench benchmark suite.

We present the modelling of embedded systems with SimBed, an execution-driven simulation testbed that measures the execution behavior and power consumption of embedded applications and RTOSs by executing them on an accurate architectural model of a microcontroller with simulated real-time stimuli. We briefly describe the simulation environment and present a study that compares three RTOSs: /spl mu/C/OS-II, a popular public-domain embedded real-time operating system; Echidna, a sophisticated, industrial-strength (commercial) RTOS; and NOS, a bare-bones multirate task scheduler reminiscent of typical "roll-your-own" RTOSs found in many commercial embedded systems. The microcontroller simulated in this study is the Motorola M-CORE processor: a low-power, 32-bit CPU core with 16-bit instructions, running at 20MHz. Our simulations show what happens when RTOSs are pushed beyond their limits and they depict situations in which unexpected interrupts or unaccounted-for task invocations disrupt timing, even when the CPU is lightly loaded. In general, there appears no clear winner in timing accuracy between preemptive systems and cooperative systems. The power-consumption measurements show that RTOS overhead is a factor of two to four higher than it needs to be, compared to the energy consumption of the minimal scheduler. In addition, poorly designed idle loops can cause the system to double its energy consumption-energy that could be saved by a simple hardware sleep mechanism.

This paper presents the modeling of embedded systems with SimBed, an execution-driven simulation testbed that measures the execution behavior and power consumption of embedded applications and RTOSs by executing them on an accurate architectural model of a microcontroller with simulated real-time stimuli. We briefly describe the simulation environment and present a study that compares three RTOSs: μC/OS-II, a popular public-domain embedded real-time operating system; Echidna, a sophisticated, industrial-strength (commercial) RTOS; and NOS, a bare-bones multi-rate task scheduler reminiscent of typical "roll-your-own" RTOSs found in many commercial embedded systems. The microcontroller simulated in this study is the Motorola M-CORE processor: a low-power, 32-bit CPU core with 16-bit instructions, running at 20MHz.