New tendencies envisage multiprocessor systems-on-chips (MPSoCs) as a promising solution for the consumer electronics market. MPSoCs are complex to design, as they must execute multiple applications (games, video) while meeting additional design constraints (energy consumption, timeto-market). Moreover, the rise of temperature in the die for MPSoCs can seriously affect their final performance and reliability. In this article, we present a new hardware-software emulation framework that allows designers a complete exploration of the thermal behavior of final MPSoC An initial version of this article was presented in the 2006 IEEE/ACM Design Automation Conference (DAC). This extended version presents several new contributions: (i) Extensions of the description of the developed thermal library and emulated SoC. (ii) Complete overview of related work on MPSoC modeling, testing and thermal-aware design. (iii) Study of different thermal library models to characterize final MPSoC designs. (iv) Illustration of the application of the tool with different floorplans. (v) Evaluation of the impact of employing different packaging technologies in target MPSoCs.

The demand for Wireless Body Sensor Networks (WBSNs) is rapidly increasing due to the revolution in wearable systems demonstrated by the penetration of on-the-body sensors in hospitals, sports medicine and general health-care practices. In WBSN, the body acts as a communication channel for the propagation of electromagnetic (EM) waves, where losses are mainly due to absorption of power in the tissue. This paper shows the effects of the dielectric properties of biological tissues in the signal strength and, for the first time, relates these effects with the human body composition. After a careful analysis of results, this work proposes a reactive algorithm for power transmission to alleviate the effect of body movement and body type. This policy achieves up to 40.8% energy savings in a realistic scenario with no performance overhead.

With the growing complexity in consumer embedded products and the improvements in process technology, Multi-Processor SystemOn-Chip (MPSoC) architectures have become widespread. These new systems are complex to design as they must execute multiple complex applications (e.g. video processing, 3D games), while meeting additional design constraints (e.g. energy consumption or time-to-market). Moreover, the rise of temperature in the die for MPSoC components can seriously affect their final performance and reliability. Therefore, mechanisms to efficiently evaluate complete HW/SW MPSoC designs in terms of energy consumption, temperature, performance and other key metrics are needed. In this paper, we present a new HW/SW FPGA-based emulation framework that allows designers to rapidly extract a number of critical statistics from processing cores, memories and interconnection systems being emulated on a FPGA. This information is then used to interact in real-time with a SW thermal model running on a host computer via an Ethernet port. The results show speed-ups of three orders of magnitude compared to cycle-accurate MPSoC simulators, which enable a very fast exploration of a large range of MPSoC design alternatives at the cycle-accurate level. Finally, our HW/SW framework allows designers to test run-time thermal management strategies with real-life inputs without any loss in the performance of the emulated system.

The time it takes software systems to be tested is usually long. Search-based test selection has been a widely investigated technique to optimize the testing process. In this paper, we propose a set of seeding strategies for the test case selection problem that generate the initial population of pareto-based multi-objective algorithms, with the goals of (1) helping to find an overall better set of solutions and (2) enhancing the convergence of the algorithms. The seeding strategies were integrated with four state-of-the-art multi-objective search algorithms and applied into two contexts where regression-testing is paramount: (1) Simulation-based testing of Cyber-Physical Systems and (2) Continuous Integration. For the first context, we evaluated our approach by using six fitness function combinations and six independent case studies, whereas in the second context we derived a total of six fitness function combinations and employed four case studies. Our evaluation suggests that some of the proposed seeding strategies are indeed helpful for solving the multi-objective test case selection problem. Specifically, the proposed seeding strategies provided a higher convergence of the algorithms towards optimal solutions in 96% of the studied scenarios and an overall cost-effectiveness with a standard search budget in 85% of the studied scenarios.

Abstract-The popularity of cloud computing has led to a dramatic increase in the number of data centers in the world. The ever-increasing computational demands along with the slowdown in technology scaling has ushered an era of power-limited servers. Techniques such as near-threshold computing (NTC) can be used to improve energy efficiency in the post-Dennard scaling era. This paper describes an architecture based on the FD-SOI process technology for near-threshold operation in servers. Our work explores the trade-offs in energy and performance when running a wide range of applications found in private and public clouds, ranging from traditional scale-out applications, such as web search or media streaming, to virtualized banking applications. Our study demonstrates the benefits of near-threshold operation and proposes several directions to synergistically increase the energy proportionality of a near-threshold server.