SACR: Scheduling-Aware Cache Reconfiguration for Real-Time Embedded Systems

Dynamic reconfiguration techniques are widely used for efficient system optimization. Dynamic cache reconfiguration is a promising approach for reducing energy consumption as well as for improving overall system performance. It is a major challenge to introduce cache reconfiguration into real-time embedded systems since dynamic analysis may adversely affect tasks with real-time constraints. This paper presents a novel approach for implementing cache reconfiguration in soft real-time systems by efficiently leveraging static analysis during execution to both minimize energy and maximize performance. To the best of our knowledge, this is the first attempt to integrate dynamic cache reconfiguration in real-time scheduling techniques. Our experimental results using a wide variety of applications have demonstrated that our approach can significantly (up to 74%) reduce the overall energy consumption of the cache hierarchy in soft real-time systems. 1

Energy-efficient Phase-based Cache Tuning for Multimedia Applications in Embedded Systems

Abstract-The proliferation of multimedia applications in embedded systems has led to a research focus on optimizing the energy consumption of these applications without significantly degrading the execution time and adhering to data processing deadline constraints. To maximize optimization potential, phasebased tuning methodologies specialize system configurations to different phases of application execution with respect to design constraints. Multimedia applications are ideal candidates for phase-based tuning since these applications exhibit variable execution characteristics. In this paper, we propose a phasebased tuning methodology for multimedia applications that leverages application characteristics to determine the best cache configurations for different phases of execution. Results reveal that phase-based tuning for multimedia applications determines cache configurations within 1% of the optimal on average and yields an average energy delay product savings of 29%

An MDP-based application oriented optimal policy for wireless sensor networks

Technological advancements due to Moore’s law have led to the proliferation of complex wireless sensor network (WSN) domains. One commonality across all WSN domains is the need to meet application requirements (i.e. lifetime, respon-siveness, etc.) through domain specific sensor node design. Techniques such as sensor node parameter tuning enable WSN designers to specialize tunable parameters (i.e. proces-sor voltage and frequency, sensing frequency, etc.) to meet these application requirements. However, given WSN do-main diversity, varying environmental situations (stimuli), and sensor node complexity, sensor node parameter tuning is a very challenging task. In this paper, we propose an auto-mated Markov Decision Process (MDP)-based methodology to prescribe optimal sensor node operation (selection of val-ues for tunable parameters such as processor voltage, pro-cessor frequency, and sensing frequency) to meet application requirements and adapt to changing environmental stimuli. Numerical results confirm the optimality of our proposed methodology and reveal that our methodology more closely meets application requirements compared to other feasible policies

An Analysis Of Work-Related Learning Literature Focusing On Race And Ethnicity

Qualitative analysis of the literature in three domains of work-related learning points to a small but growing number of studies and conceptual articles focusing explicitly on race/ethnicity. Findings varied across the three domains of continuing professional education, human research development, and workforce development

The Influence of Obesity-Related Single Nucleotide Polymorphisms on BMI Across the Life Course: The PAGE Study

Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18–100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18–25 years), adulthood (ages 26–49 years), middle-age adulthood (ages 50–69 years), and older adulthood (ages ≥70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m2, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy