Learning to Rank Graph-based Application Objects on Heterogeneous Memories

Persistent Memory (PMEM), also known as Non-Volatile Memory (NVM), can deliver higher density and lower cost per bit when compared with DRAM. Its main drawback is that it is typically slower than DRAM. On the other hand, DRAM has scalability problems due to its cost and energy consumption. Soon, PMEM will likely coexist with DRAM in computer systems but the biggest challenge is to know which data to allocate on each type of memory. This paper describes a methodology for identifying and characterizing application objects that have the most influence on the application's performance using Intel Optane DC Persistent Memory. In the first part of our work, we built a tool that automates the profiling and analysis of application objects. In the second part, we build a machine learning model to predict the most critical object within large-scale graph-based applications. Our results show that using isolated features does not bring the same benefit compared to using a carefully chosen set of features. By performing data placement using our predictive model, we can reduce the execution time degradation by 12\% (average) and 30\% (max) when compared to the baseline's approach based on LLC misses indicator

Testing in resource constrained execution environments

Software for resource constrained embedded devices is often implemented in the Java programming language because the Java compiler and virtual machine provide enhanced safety, portability, and the potential for run-time optimization. It is important to verify that a software application executes correctly in the environment in which it will normally execute, even if this environment is an embedded one that severely constrains memory resources. Testing can be used to isolate defects within and establish a confidence in the correctness of a Java application that executes in a resource constrained environment. However, executing test suites with a Java virtual machine (JVM) that uses dynamic compilation to create native code bodies can introduce significant testing time overheads if memory resources are highly constrained. This paper describes an approach that uses adaptive code unloading to ensure that it is feasible to perform testing in the actual memory constrained execution environment. The experiments demonstrate that code unloading can reduce both the test suite execution time by 34 % and the code size of the test suite and application under test by 78 % while maintaining the overall size of the JVM. Categories and Subject Descriptors: D.2.5 [Software Engineering]: Testing and Debugging-Testing tools; D.3.4 [Programming Languages]: Processors-code generation

Data Supplement for the IGSC 2019 paper ``A benchmark suite for control algorithms of retractable wind-energy harvesters''

The following files comprise the Data Supplement to which the IGSC 2019* paper ``A benchmark suite for control algorithms of retractable wind-energy harvesters'' refers: 1) Thirty training and testing files, each with approximately nine and two years, respectively, of minute-by-minute windspeeds and simulated predicted day-ahead windspeeds; 2) An eleven-year hourly electricity price file; 3) A fuzzy-set-membership-function file describing membership in the set NOT WINDY AT for each of the 30 weather stations; 4) A file containing sunset times for the city of St. Louis, Missouri, for all days in the years 2004-2014, inclusive, which are used in the definition of quiet hours for St. Louis; 5) A file delineating when noise is allowed for municipalities corresponding to the 30 weather stations; and 6) A document describing how the windspeed data was derived. *The Tenth International Green and Sustainable Computing Conferenc

Advanced Magnetics for Power and Energy Development - A Multidisciplinary Consortium between the University of Pittsburgh, Carnegie Mellon University, and North Carolina State University

Emerging societal trends drive the need for advanced magnetic materials and power magnetic components including the electrification of domestic and military transportation; the emergence of solid state transformers as a practical and viable alternative to conventional transformers; increased penetration of renewables and other distributed energy resources which require power electronics converters and novel electric machines for grid integration. A historical gap in research and development funding for advanced power magnetics has created a severe shortfall in the necessary workforce required to support these quickly emerging areas within both nascent and established industries in the electric power sector. Since January 2020, faculty members in the engineering school having been establishing a consortium called Advanced Magnetics for Power and Energy Development (AMPED). The consortium will focus on magnetic materials development, manufacturing techniques, and their utilization in power electronic systems at medium frequency and medium power levels. Other AMPED university partners include North Carolina State University and Carnegie Mellon University. Faculty from the School of Engineering will lead this proposal effort with support from the Katz School of Business and School of Computing and Information Science. Faculty from the Katz School of Business will offer expertise in technology-to-market planning and competitive analysis, and faculty from the School of Computing and Information will aid in the development of novel algorithms for optimizing magnetics and power electronics technology like transformers, inductors, and electric motors given cost, weight, performance and volume constraints. The faculty received $60,000 to establish synergies through facilitated team collaborations, supporting graduate student stipends, and investing into laboratory space at the Energy GRID Institute. The first goal will be to submit concept papers followed by full proposals for attracting federal dollars from the DoE, DoD, or NSF. The second goal will be to attract$100,000 in company investment for AMPED through the membership model

Randomised feasibility trial of the helping families programme-modified: an intensive parenting intervention for parents affected by severe personality difficulties.

BACKGROUND: Specialist parenting intervention could improve coexistent parenting and child mental health difficulties of parents affected by severe personality difficulties. OBJECTIVE: Conduct a feasibility trial of Helping Families Programme-Modified (HFP-M), a specialist parenting intervention. DESIGN: Pragmatic, mixed-methods trial, 1:1 random allocation, assessing feasibility, intervention acceptability and outcome estimates. SETTINGS: Two National Health Service health trusts and local authority children's social care. PARTICIPANTS: Parents: (i) primary caregiver, (ii) 18 to 65 years, (iii) severe personality difficulties, (iv) proficient English and (v) capacity for consent. Child: (i) 3 to 11 years, (ii) living with index parent and (iii) significant emotional/behavioural difficulties. INTERVENTION: HFP-M: 16-session home-based intervention using parenting and therapeutic engagement strategies. Usual care: standard care augmented by single psychoeducational parenting session. OUTCOMES: Primary feasibility outcome: participant retention rate. SECONDARY OUTCOMES: (i) rates of recruitment, eligibility and data completion, and (ii) rates of intervention acceptance, completion and alliance (Working Alliance Inventory-Short Revised). Primary clinical outcome: child behaviour (Eyberg Child Behaviour Inventory). SECONDARY OUTCOMES: child mental health (Concerns About My Child, Child Behaviour Checklist-Internalising Scale), parenting (Arnold-O'Leary Parenting Scale, Kansas Parental Satisfaction Scale) and parent mental health (Symptom-Checklist-27). Quantitative data were collected blind to allocation. RESULTS: Findings broadly supported non-diagnostic selection criterion. Of 48 participants recruited, 32 completed post-intervention measures at mean 42 weeks later. Participant retention exceeded a priori rate (HFP-M=18; Usual care=14; 66.7%, 95% CI 51.6% to 79.6%). HFP-M was acceptable, with delivery longer than planned. Usual care had lower alliance rating. Child and parenting outcome effects detected across trial arms with potential HFP-M advantage (effect size range: 0.0 to 1.3). CONCLUSION: HFP-M is an acceptable and potentially effective specialist parenting intervention. A definitive trial is feasible, subject to consideration of recruitment and retention methods, intervention efficiency and comparator condition. Caution is required in interpretation of results due to reduced sample size. No serious adverse events reported. TRIAL REGISTRATION NUMBER: ISRCTN14573230

Seamless Integration of Heterogeneous Devices and Access Control in Smart Homes

Abstract—The recent trend of ubiquitous access to embedded physical devices over the Internet as well as increasing penetration of wireless protocols such as ZigBee has raised attention to smart homes. These systems consist of sensors, devices and smart appliances that can be monitored and controlled remotely by human users and cloud services. However, the lack of a de facto communication standard for smart homes creates a barrier against the interoperability of devices from different vendors. We address this challenge by proposing a holistic, extensible software architecture that seamlessly integrates heterogeneous protocol- and vendor-specific devices and services, while making these services securely available over the Internet. Our architecture is developed on top of the OSGi framework and incorporates a semantic model of a smart home system. As a result, we achieve semantic interoperability – the ability to integrate new applications and drivers into the deployed system during runtime. Furthermore, we integrate a new access control model for specific smart home scenarios. As a proof of our concept, we demonstrate the seamless semantic discovery of home devices at runtime by integrating several protocols including X10, Insteon, ZigBee and UPnP into a real test. Using smart phones and cloud services together with our home gateway implementation, we further demonstrate the ease of integration of new applications and drivers. Keywords- smart home; interoperation; semantics; access control I

‘It Takes Two Hands to Clap’: How Gaddi Shepherds in the Indian Himalayas Negotiate Access to Grazing

This article examines the effects of state intervention on the workings of informal institutions that coordinate the communal use and management of natural resources. Specifically it focuses on the case of the nomadic Gaddi shepherds and official attempts to regulate their access to grazing pastures in the Indian Himalayas. It is often predicted that the increased presence of the modern state critically undermines locally appropriate and community-based resource management arrangements. Drawing on the work of Pauline Peters and Francis Cleaver, I identify key instances of socially embedded ‘common’ management institutions and explain the evolution of these arrangements through dynamic interactions between individuals, communities and the agents of the state. Through describing the ‘living space’ of Gaddi shepherds across the annual cycle of nomadic migration with their flocks I explore the ways in which they have been able to creatively reinterpret external interventions, and suggest how contemporary arrangements for accessing pasture at different moments of the annual cycle involve complex combinations of the formal and the informal, the ‘traditional’ and the ‘modern’