Mely: Efficient Workstealing for Multicore Event-Driven Systems

Many high-performance communicating systems are designed using the event-driven paradigm. As multicore platforms are now pervasive, it becomes crucial for such systems to take advantage of the available hardware parallelism. Event-coloring is a promising approach in this regard. First, it allows programmers to simply and progressively inject support for the safe, parallel execution of multiple event handlers through the use of annotations. Second, it relies on a workstealing algorithm to dynamically balance the execution of event handlers on the available cores. This paper studies the impact of the workstealing algorithm on the overall system performance. We first show that the only existing workstealing algorithm designed for event-coloring runtimes is not always efficient: for instance, it causes a 33% performance degradation on a Web server. We then introduce several enhancements to improve the workstealing behavior. An evaluation using both microbenchmarks and real applications, a Web server and the Secure File Server (SFS), shows that our system consistently outperforms a state-of-the-art runtime (Libasync-smp), with or without workstealing. In particular, our new workstealing improves performance by up to +25% compared to Libasync-smp without workstealing and by up to +73% compared to the Libasync-smp workstealing algorithm, in the Web server case

C-Stream: A coroutine-based elastic stream processing engine

Cataloged from PDF version of article.Stream processing is a computational paradigm for on-the-fly processing of live data. This paradigm lends itself to implementations that can provide high throughput and low latency, by taking advantage of various forms of parallelism that is naturally captured by the stream processing model of computation, such as pipeline, task, and data parallelism. In this thesis, we describe the design and implementation of C-Stream, which is an elastic stream processing engine. C-Stream encompasses three unique properties. First, in contrast to the widely adopted event-based interface for developing stream processing operators, C-Stream provides an interface wherein each operator has its own control loop and rely on data availability APIs to decide when to perform its computations. The self-control based model significantly simplifies development of operators that require multi-port synchronization. Second, C-Stream contains a multi-threaded dynamic scheduler that manages the execution of the operators. The scheduler, which is customizable via plug-ins, enables the execution of the operators as co-routines, using any number of threads. The base scheduler implements back-pressure, provides data availability APIs, and manages preemption and termination handling. Last, C-Stream provides elastic parallelization. It can dynamically adjust the number of threads used to execute an application, and can also adjust the number of replicas of data-parallel operators to resolve bottlenecks. We provide an experimental evaluation of C-Stream. The results show that C-Stream is scalable, highly customizable, and can resolve bottlenecks by dynamically adjusting the level of data parallelism used.Şahin, SemihM.S

Compiling functional reactive macroprograms for sensor networks

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 77-79).Sensor networks present a number of novel programming challenges for application developers. Their inherent limitations of computational power, communication bandwidth, and energy demand new approaches to programming that shield the developer from low-level details of resource management, concurrency, and in-network processing. To answer this challenge, this thesis presents a functional macroprogramming language called Regiment. The essential data model in Regiment is based on regions, which represent spatially distributed, time-varying collections of state. The programmer uses regions to define and manipulate dynamic sets of sensor nodes. A first compiler for Regiment has been constructed, which implements the essential core of the language on the TinyOS platform. This thesis presents the compiler as well as an intermediate language developed to serve as a Regiment compilation target.by Ryan Rhodes Newton.S.M

Enhancing user's privacy : developing a model for managing and testing the lifecycle of consent and revocation

Increasingly, people turn to the Internet for access to services, which often require disclosure of a significant amount of personal data. Networked technologies have enabled an explosive growth in the collection, storage and processing of personal information with notable commercial potential. However, there are asymmetries in relation to how people are able to control their own information when handled by enterprises. This raises significant privacy concerns and increases the risk of privacy breaches, thus creating an imperative need for mechanisms offering information control functionalities. To address the lack of controls in online environments, this thesis focuses on consent and revocation mechanisms to introduce a novel approach for controlling the collection, usage and dissemination of personal data and managing privacy ex- pectations. Drawing on an extensive multidisciplinary review on privacy and on empirical data from focus groups, this research presents a mathematical logic as the foundation for the management of consent and revocation controls in technological systems. More specifically, this work proposes a comprehensive conceptual model for con- sent and revocation and introduces the notion of 'informed revocation'. Based on this model, a Hoare-style logic is developed to capture the effects of expressing indi- viduals' consent and revocation preferences. The logic is designed to support certain desirable properties, defined as healthiness conditions. Proofs that these conditions hold are provided with the use of Maude software. This mathematical logic is then verified in three real-world case study applications with different consent and revocation requirements for the management of employee data in a business envi- ronment, medical data in a biobank and identity assurance in government services. The results confirm the richness and the expressiveness of the logic. In addition, a novel testing strategy underpinned by this logic is presented. This strategy is able to generate testing suites for systems offering consent and revocation controls, such as the EnCoRe system, where testing was carried out successfully and resulted in identifying faults in the EnCoRe implementation

Enhancing Usability and Explainability of Data Systems

The recent growth of data science expanded its reach to an ever-growing user base of nonexperts, increasing the need for usability, understandability, and explainability in these systems. Enhancing usability makes data systems accessible to people with different skills and backgrounds alike, leading to democratization of data systems. Furthermore, proper understanding of data and data-driven systems is necessary for the users to trust the function of the systems that learn from data. Finally, data systems should be transparent: when a data system behaves unexpectedly or malfunctions, the users deserve proper explanation of what caused the observed incident. Unfortunately, most existing data systems offer limited usability and support for explanations: these systems are usable only by experts with sound technical skills, and even expert users are hindered by the lack of transparency into the systems\u27 inner workings and functions. The aim of my thesis is to bridge the usability gap between nonexpert users and complex data systems, aid all sort of users, including the expert ones, in data and system understanding, and provide explanations that help reason about unexpected outcomes involving data systems. Specifically, my thesis has the following three goals: (1) enhancing usability of data systems for nonexperts, (2) enable data understanding that can assist users in a variety of tasks such as achieving trust in data-driven machine learning, gaining data understanding, and data cleaning, and (3) explaining causes of unexpected outcomes involving data and data systems. For enhancing usability, we focus on example-driven user intent discovery. We develop systems based on example-driven interactions in two different settings: querying relational databases and personalized document summarization. Towards data understanding, we develop a new data-profiling primitive that can characterize tuples for which a machine-learned model is likely to produce untrustworthy predictions. We also develop an explanation framework to explain causes of such untrustworthy predictions. Additionally, this new data-profiling primitive enables interactive data cleaning. Finally, we develop two explanation frameworks, tailored to provide explanations in debugging data system components, including the data itself. The explanation frameworks focus on explaining the root cause of a concurrent application\u27s intermittent failure and exposing issues in the data that cause a data-driven system to malfunction

Performance Comparison of Uniprocessor and Multiprocessor Web Server Architectures

This thesis examines web-server architectures for static workloads on both uniprocessor and multiprocessor systems to determine the key factors affecting their performance. The architectures examined are event-driven (userver) and pipeline (WatPipe). As well, a thread-per-connection (Knot) architecture is examined for the uniprocessor system. Various workloads are tested to determine their effect on the performance of the servers. Significant effort is made to ensure a fair comparison among the servers. For example, all the servers are implemented in C or C++, and support sendfile and edge-triggered epoll. The existing servers, Knot and userver, are extended as necessary, and the new pipeline-server, WatPipe, is implemented using userver as its initial code base. Each web server is also tuned to determine its best configuration for a specific workload, which is shown to be critical to achieve best server performance. Finally, the server experiments are verified to ensure each is performing within reasonable standards. The performance of the various architectures is examined on a uniprocessor system. Three workloads are examined: no disk-I/O, moderate disk-I/O and heavy disk-I/O. These three workloads highlight the differences among the architectures. As expected, the experiments show the amount of disk I/O is the most significant factor in determining throughput, and once there is memory pressure, the memory footprint of the server is the crucial performance factor. The peak throughput differs by only 9-13% among the best servers of each architecture across the various workloads. Furthermore, the appropriate configuration parameters for best performance varied based on workload, and no single server performed the best for all workloads. The results show the event-driven and pipeline servers have equivalent throughput when there is moderate or no disk-I/O. The only difference is during the heavy disk-I/O experiments where WatPipe's smaller memory footprint for its blocking server gave it a performance advantage. The Knot server has 9% lower throughput for no disk-I/O and moderate disk-I/O and 13% lower for heavy disk-I/O, showing the extra overheads incurred by thread-per-connection servers, but still having performance close to the other server architectures. An unexpected result is that blocking sockets with sendfile outperforms non-blocking sockets with sendfile when there is heavy disk-I/O because of more efficient disk access. Next, the performance of the various architectures is examined on a multiprocessor system. Knot is excluded from the experiments as its underlying thread library, Capriccio, only supports uniprocessor execution. For these experiments, it is shown that partitioning the system so that server processes, subnets and requests are handled by the same CPU is necessary to achieve high throughput. Both N-copy and new hybrid versions of the uniprocessor servers, extended to support partitioning, are tested. While the N-copy servers performed the best, new hybrid versions of the servers also performed well. These hybrid servers have throughput within 2% of the N-copy servers but offer benefits over N-copy such as a smaller memory footprint and a shared address-space. For multiprocessor systems, it is shown that once the system becomes disk bound, the throughput of the servers is drastically reduced. To maximize performance on a multiprocessor, high disk throughput and lots of memory are essential

Faculty Publications and Creative Works 2004

Faculty Publications & Creative Works is an annual compendium of scholarly and creative activities of University of New Mexico faculty during the noted calendar year. Published by the Office of the Vice President for Research and Economic Development, it serves to illustrate the robust and active intellectual pursuits conducted by the faculty in support of teaching and research at UNM

Undergraduate Student Catalog 2020-2021

The central pillars of Qatar University’s mission are highlighted through this document, namely the provision of high-quality education and the pursuit of an active role in the development of Qatari society. The courses described here have been designed, reviewed and assessed to meet the highest educational standards, with a strong focus on the knowledge and skill-based learning that is needed for a graduate to be competitive in today’s labor market and in graduate education pursuits. The many of the academic programs have attained independent external accreditation from internationally recognized associations, to cater to the needs of the country’s ambitious development course