Scaling Causality Analysis for Production Systems.

Causality analysis reveals how program values influence each other. It is important for debugging, optimizing, and understanding the execution of programs. This thesis scales causality analysis to production systems consisting of desktop and server applications as well as large-scale Internet services. This enables developers to employ causality analysis to debug and optimize complex, modern software systems. This thesis shows that it is possible to scale causality analysis to both fine-grained instruction level analysis and analysis of Internet scale distributed systems with thousands of discrete software components by developing and employing automated methods to observe and reason about causality. First, we observe causality at a fine-grained instruction level by developing the first taint tracking framework to support tracking millions of input sources. We also introduce flexible taint tracking to allow for scoping different queries and dynamic filtering of inputs, outputs, and relationships. Next, we introduce the Mystery Machine, which uses a ``big data'' approach to discover causal relationships between software components in a large-scale Internet service. We leverage the fact that large-scale Internet services receive a large number of requests in order to observe counterexamples to hypothesized causal relationships. Using discovered casual relationships, we identify the critical path for request execution and use the critical path analysis to explore potential scheduling optimizations. Finally, we explore using causality to make data-quality tradeoffs in Internet services. A data-quality tradeoff is an explicit decision by a software component to return lower-fidelity data in order to improve response time or minimize resource usage. We perform a study of data-quality tradeoffs in a large-scale Internet service to show the pervasiveness of these tradeoffs. We develop DQBarge, a system that enables better data-quality tradeoffs by propagating critical information along the causal path of request processing. Our evaluation shows that DQBarge helps Internet services mitigate load spikes, improve utilization of spare resources, and implement dynamic capacity planning.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135888/1/mcchow_1.pd

Energy-Efficient Acceleration of Asynchronous Programs.

Asynchronous or event-driven programming has become the dominant programming model in the last few years. In this model, computations are posted as events to an event queue from where they get processed asynchronously by the application. A huge fraction of computing systems built today use asynchronous programming. All the Web 2.0 JavaScript applications (e.g., Gmail, Facebook) use asynchronous programming. There are now more than two million mobile applications available between the Apple App Store and Google Play, which are all written using asynchronous programming. Distributed servers (e.g., Twitter, LinkedIn, PayPal) built using actor-based languages (e.g., Scala) and platforms such as node.js rely on asynchronous events for scalable communication. Internet-of-Things (IoT), embedded systems, sensor networks, desktop GUI applications, etc., all rely on the asynchronous programming model. Despite the ubiquity of asynchronous programs, their unique execution characteristics have been largely ignored by conventional processor architectures, which have remained heavily optimized for synchronous programs. Asynchronous programs are characterized by short events executing varied tasks. This results in a large instruction footprint with little cache locality, severely degrading cache performance. Also, event execution has few repeatable patterns causing poor branch prediction. This thesis proposes novel processor optimizations exploiting the unique execution characteristics of asynchronous programs for performance optimization and energy-efficiency. These optimizations are designed to make the underlying hardware aware of discrete events and thereafter, exploit the latent Event-Level Parallelism present in these applications. Through speculative pre-execution of future events, cache addresses and branch outcomes are recorded and later used for improving cache and branch predictor performance. A hardware instruction prefetcher specialized for asynchronous programs is also proposed as a comparative design direction.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120780/1/gauravc_1.pd

Energy efficient run-time mapping and thread partitioning of concurrent OpenCL applications on CPU-GPU MPSoCs

Heterogeneous Multi-Processor Systems-on-Chips (MPSoCs) containing CPU and GPU cores are typically required to execute applications concurrently. However, as will be shown in this paper, existing approaches are not well suited for concurrent applications as they are developed either by considering only a single application or they do not exploit both CPU and GPU cores at the same time. In this paper, we propose an energy-efficient run-time mapping and thread partitioning approach for executing concurrent OpenCL applications on both GPU and GPU cores while satisfying performance requirements. Depending upon the performance requirements, for each concurrently executing application, the mapping process finds the appropriate number of CPU cores and operating frequencies of CPU and GPU cores, and the partitioning process identifies an efficient partitioning of the applications’ threads between CPU and GPU cores. We validate the proposed approach experimentally on the Odroid-XU3 hardware platform with various mixes of applications from the Polybench benchmark suite. Additionally, a case-study is performed with a real-world application SLAMBench. Results show an average energy saving of 32% compared to existing approaches while still satisfying the performance requirements

Advising Minority Pre-Med Students: Perceptions of Pre-Med Advisors at Institutions in the Southeastern Association of Advisors in the Health Professions Region

The purpose of this qualitative study was to explore pre-medical advisors’ perceptions on their role in the pathway to medicine for students historically underrepresented in medicine (URiM) and to gain insight into barriers these students face. While a small amount of research exists on the perspective of URiM pre-medical students on the pathway to medicine, no analysis has been conducted on the role pre-medical advisors play. The underlying framework of this research study focused on the experience of advisors through the lens of academic advising approaches, self-authorship theory, and capital theory to make a strong collective framework to begin understanding the role of advising in the pathway. Data were gathered through interviews using a non-random purposeful sampling strategy. Study participants were pre-medical advisors at undergraduate institutions in the SAAHP. Participants discussed their role in the pre-medical pathway for URiM students, advising approaches they employ, and their advising experience. Key themes emerged during data analysis. Advisors tend to approach their student encounters as individual experiences but draw from a variety of advising approaches. URiM students experiences a variety of barriers but most frequently encounter financial barriers, academic challenges, and concerns over lack of belonging. Advisors face a variety of challenges in addressing barriers faced by URiM students. Advisors indicated that early intervention for academic support, collaboration with others tangential to the process, and more visibility for URiM students were approaches that would help retain URiM students on the path to medicine. There is perceived value in utilizing the role of pre-medical advisors as a method of support to keep URiM students moving forward as they can both an advocate for their success and help them navigate the challenge of being a pre-medical student

Accurate Power Consumption Evaluation forPeripherals in Ultra Low-Power embedded systems

International audienceWe propose a methodology to measure, model and simulate power consumption of peripheral devices of a lowpower embedded micro-controller, while keeping a reasonable development cost. This methodology is experimented against the low-power MSP-EXP430FR5739 platform that includes nonvolatile RAM for intermittent computing purposes and a handful of peripherals. The experimental measurements enable the characterization of the consumption of the peripherals, while many existing comparable studies do not provide power consumption for peripherals. These measurements are integrated into a simulator that targets low-power peripheral-intensive applications, as are most of IoT embedded programs. The accuracy of the power consumption estimation is within a 5% error on intermittent embedded computing using peripherals

The Circuit, Spring 2018

Table of Contents: Fugere Generosity Creates Opportunities Faculty News Sparsifying Graphs for Faster Data Processing Manipulating Electromagnetic Waves by Artificial Materials Taking a Close Look at Computing COVOX is My Co-Pilot Taking on New Departmental Roles Student News Alumni Spotlighthttps://digitalcommons.mtu.edu/ece-newsletters/1005/thumbnail.jp

The Home Program Adherence Tackle Box: A Fishing-Themed Toolkit for Rehabilitation Clinicians

Background: Home programs (HPs) are an important part of the rehabilitation experience and are regularly recommended by occupational therapy practitioners (OTPs) and other rehabilitation clinicians for continuation and supplementation of care, to address a client’s continual needs at home and in the community (DeForge et al., 2008; Donoso Brown, & Fichter, 2017; Emmerson et al., 2017; Picha, & Howell, 2018; Proffitt, 2016). Home programs created by rehabilitation professionals for clients typically include therapeutic exercises, activities, and lifestyle behavior modifications to compliment treatment and/or discharge recommendations. Issuing home programs is an established standard of care to help clients meet targeted client goals and outcomes (Proffitt, 2016). The data in the literature suggests that rates of adherence to rehabilitation home programs are lower than acceptable ranging from 40-70% across various populations (DeForge et al., 2008; Donoso Brown, & Fichter, 2017; Emmerson et al., 2017; Picha, & Howell, 2018; Proffitt, 2016). According to the World Health Organization (2003), adherence is considered a key factor influencing treatment effectiveness and optimal client outcomes, especially when considering lifestyle interventions. Adherence is a complex and multifactorial issue, which may explain why it goes largely unaddressed by practitioners due to the many associated barriers of healthcare systems, providers, and clients (WHO, 2016). Currently, literature is limited regarding occupational therapy’s role in assessing and addressing barriers to home program adherence. Purpose: The purpose of this scholarly project was to develop a user-friendly guide and toolkit designed for rehabilitation practitioners to therapeutically “tackle” the complex, multifactorial challenges and barriers associated with a client’s adherence to HPs, many of which are potentially modifiable with targeted interventions (Picha, & Howell, 2018). Methods: The contributing developers of this product conducted an extensive literature review to determine: (1) current use and prescription of HPs in rehabilitation; (2) barriers and facilitators of adherence to HPs; (3) current use of adherence tools used in rehabilitation; and (4) best practice principles for promoting adherence for HPs. Conclusion: The results of the literature review guided the development of the product, the Home Program Adherence Tackle Box. The Home Program Adherence Tackle Box contains client centered strategies and critical guiding resources that OTPs, and other clinical rehabilitation enthusiasts, can use to skillfully facilitate client adherence to home program recommendations to enhance one\u27s function and occupations in life. This themed booklet includes evidence-based strategies and intervention resources to help efficiently guide rehabilitation professionals in holistically promoting HP adherence. It includes the development, collection, and organization of a multitude of relevant tackle tools