Cycle Accurate Energy and Throughput Estimation for Data Cache

Resource optimization in energy constrained real-time adaptive embedded systems highly depends on accurate energy and throughput estimates of processor peripherals. Such applications require lightweight, accurate mathematical models to profile energy and timing requirements on the go. This paper presents enhanced mathematical models for data cache energy and throughput estimation. The energy and throughput models were found to be within 95% accuracy of per instruction energy model of a processor, and a full system simulator?s timing model respectively. Furthermore, the possible application of these models in various scenarios is discussed in this paper

Data Cache-Energy and Throughput Models: Design Exploration for Embedded Processors

Most modern 16-bit and 32-bit embedded processors contain cache memories to further increase instruction throughput of the device. Embedded processors that contain cache memories open an opportunity for the low-power research community to model the impact of cache energy consumption and throughput gains. For optimal cache memory configuration mathematical models have been proposed in the past. Most of these models are complex enough to be adapted for modern applications like run-time cache reconfiguration. This paper improves and validates previously proposed energy and throughput models for a data cache, which could be used for overhead analysis for various cache types with relatively small amount of inputs. These models analyze the energy and throughput of a data cache on an application basis, thus providing the hardware and software designer with the feedback vital to tune the cache or application for a given energy budget. The models are suitable for use at design time in the cache optimization process for embedded processors considering time and energy overhead or could be employed at runtime for reconfigurable architectures

One-Hop Throughput of Wireless Networks with Random Connections

We consider one-hop communication in wireless networks with random connections. In the random connection model, the channel powers between different nodes are drawn from a common distribution in an i.i.d. manner. An scheme achieving the throughput scaling of order $n^{1/3-\delta}$, for any $\delta>0$, is proposed, where $n$ is the number of nodes. Such achievable throughput, along with the order $n^{1/3}$ upper bound derived by Cui et al., characterizes the throughput capacity of one-hop schemes for the class of connection models with finite mean and variance.Comment: Submitted to IEEE Communications Letter

HeCSON: Heuristic for Configuration Selectionin Optical Network Planning

We present a transceiver configuration selection heuristic combining Enhanced Gaussian Noise (EGN) models, which shows a 40\% increase in throughput and 87\% decrease in execution time, compared to only approximate EGN and Full-Form EGN respectively

Exploring the link between port throughput and economic activity : some comments on space- and time-related issues

The link between economic activity and (freight) transport is a classic issue in regional science. A subtopic is the impact of economic activity on the demand for maritime transport through ports. Understanding this relationship contributes to a better understanding of the dynamics of port throughput, which is important for infrastructure planning and other strategic decisions. This paper focuses on the port of Antwerp (Belgium) and explores the link between port throughput and GDP. An exploratory analysis reveals that not only the GDP of Belgium matters, but also that of neighbouring countries. Furthermore, different results are obtained for different commodity groups, and the most appropriate time-lag is not the same for each country. On the basis of these findings, we formulate some recommendations for port throughput models