Alberto Macii

Bio: Alberto Macii is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Battery (electricity) & Low-power electronics. The author has an hindex of 29, co-authored 161 publications receiving 2784 citations. Previous affiliations of Alberto Macii include Seoul National University.

A discrete-time battery model for high-level power estimation

Abstract: In this paper, we introduce a discrete-time model for the complete power supply sub-system that closely approximates the behavior of its circuit-level (i.e., HSpice), continuous-time counterpart. The model is abstract and efficient enough to enable event-driven simulation of digital systems described at a very high level of abstraction and that include, among their components, also the power supply. Therefore, it can be successfully used for the purpose of battery life-time estimation during design optimization, as shown by the results we have collected on a meaningful case study. Experiments prove also that the accuracy of our model is very close to that provided by the corresponding Spice-level model.

Discrete-time battery models for system-level low-power design

Abstract: For portable applications, long battery lifetime is the ultimate design goal. Therefore, the availability of battery and voltage converter models providing accurate estimates of battery lifetime is key for system-level low-power design frameworks. In this paper, we introduce a discrete-time model for the complete power supply subsystem that closely approximates the behavior of its circuit-level continuous-time counterpart. The model is abstract and efficient enough to enable event-driven simulation of digital systems described at a very high level of abstraction and that includes, among their components, also the power supply. The model gives the designer the possibility of estimating battery lifetime during system-level design exploration, as shown by the results we have collected on meaningful case studies. In addition, it is flexible and it can thus be employed for different battery chemistries.

Selective instruction compression for memory energy reduction in embedded systems

Abstract: Proposes a technique for reducing the energy required by firmware code to execute on embedded systems. The method is based on the idea of compressing the most commonly executed instructions so as to reduce the energy dissipated in memory accesses. Instruction decompression is performed on the fly by a hardware module located between processor and memory: no changes to the processor architecture are required. Hence, our technique is well-suited for systems employing IP (instruction processor) cores whose internal architecture cannot be modified. We describe a number of decompression schemes and architectures that effectively trade hardware complexity for memory energy and bandwidth reduction, as proved by experimental data collected by executing several sample programs.

Architectures and synthesis algorithms for power-efficient bus interfaces

Abstract: In this paper we present algorithms for the synthesis of encoding and decoding interface logic that minimizes the average number of transitions on heavily-loaded global bus lines at no cost in communication throughput (i.e., one word is transmitted at each cycle). The distinguishing feature of our approach is that it does not rely on designer's intuition, but it automatically constructs low-transition activity codes and hardware implementation of encoders and decoders, given information on word-level statistics. We propose an accurate method that is applicable to low-width buses, as well as approximate methods that scale well with bus width. Furthermore, we introduce an adaptive architecture that automatically adjusts encoding to reduce transition activity on buses whose word-level statistics are not known a priori. Experimental results demonstrate that our approaches out-perform specialized low-power encoding schemes presented in the past.

Battery-driven dynamic power management

Abstract: Battery lifetime extension is a primary design objective for portable systems. We introduce the concept of battery-driven dynamic power management, which strives to enhance lifetime by automatically adapting discharge rate and current profiles to battery charge state.

[서평]「Applied Cryptography」

Abstract: The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

Accurate electrical battery model capable of predicting runtime and I-V performance

Abstract: Low power dissipation and maximum battery runtime are crucial in portable electronics. With accurate and efficient circuit and battery models in hand, circuit designers can predict and optimize battery runtime and circuit performance. In this paper, an accurate, intuitive, and comprehensive electrical battery model is proposed and implemented in a Cadence environment. This model accounts for all dynamic characteristics of the battery, from nonlinear open-circuit voltage, current-, temperature-, cycle number-, and storage time-dependent capacity to transient response. A simplified model neglecting the effects of self-discharge, cycle number, and temperature, which are nonconsequential in low-power Li-ion-supplied applications, is validated with experimental data on NiMH and polymer Li-ion batteries. Less than 0.4% runtime error and 30-mV maximum error voltage show that the proposed model predicts both the battery runtime and I-V performance accurately. The model can also be easily extended to other battery and power sourcing technologies.

Power efficient organization of wireless sensor networks

Abstract: Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical environments. One of the major challenges in devising such networks lies in the constrained energy and computational resources available to sensor nodes. These constraints must be taken into account at all levels of the system hierarchy. The deployment of sensor nodes is the first step in establishing a sensor network. Since sensor networks contain a large number of sensor nodes, the nodes must be deployed in clusters, where the location of each particular node cannot be fully guaranteed a priori. Therefore, the number of nodes that must be deployed in order to completely cover the whole monitored area is often higher than if a deterministic procedure were used. In networks with stochastically placed nodes, activating only the necessary number of sensor nodes at any particular moment can save energy. We introduce a heuristic that selects mutually exclusive sets of sensor nodes, where the members of each of those sets together completely cover the monitored area. The intervals of activity are the same for all sets, and only one of the sets is active at any time. The experimental results demonstrate that by using only a subset of sensor nodes at each moment, we achieve a significant energy savings while fully preserving coverage.