Operating System Contribution to Composable Timing Behaviour in High-Integrity Real-Time Systems

The development of High-Integrity Real-Time Systems has a high footprint in terms of human, material and schedule costs. Factoring functional, reusable logic in the application favors incremental development and contains costs. Yet, achieving incrementality in the timing behavior is a much harder problem. Complex features at all levels of the execution stack, aimed to boost average-case performance, exhibit timing behavior highly dependent on execution history, which wrecks time composability and incrementaility with it. Our goal here is to restitute time composability to the execution stack, working bottom up across it. We first characterize time composability without making assumptions on the system architecture or the software deployment to it. Later, we focus on the role played by the real-time operating system in our pursuit. Initially we consider single-core processors and, becoming less permissive on the admissible hardware features, we devise solutions that restore a convincing degree of time composability. To show what can be done for real, we developed TiCOS, an ARINC-compliant kernel, and re-designed ORK+, a kernel for Ada Ravenscar runtimes. In that work, we added support for limited-preemption to ORK+, an absolute premiere in the landscape of real-word kernels. Our implementation allows resource sharing to co-exist with limited-preemptive scheduling, which extends state of the art. We then turn our attention to multicore architectures, first considering partitioned systems, for which we achieve results close to those obtained for single-core processors. Subsequently, we shy away from the over-provision of those systems and consider less restrictive uses of homogeneous multiprocessors, where the scheduling algorithm is key to high schedulable utilization. To that end we single out RUN, a promising baseline, and extend it to SPRINT, which supports sporadic task sets, hence matches real-world industrial needs better. To corroborate our results we present findings from real-world case studies from avionic industry

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Memory-aware platform description and framework for source-level embedded MPSoC software optimization

Developing optimizing source-level transformations, consists of numerous non-trivial subtasks. Besides identifying actual optimization goals within a particular target-platform and compiler setup, the actual implementation is a tedious, error-prone and often recurring work. Providing appropriate support for this development work is a challenging task. Defining and implementing a well-suited target-platform description which can be used by a wide set of optimization techniques while being precise and easy to maintain is one dimension of this challenging task. Another dimension, which has also been tackled in this work, deals with provision of an infrastructure for optimization-step representation, interaction and data retention. Finally, an appropriate source-code representation has been integrated into this approach. These contributions are tightly related to each other, they have been bundled into the MACCv2 framework, a fullfledged optimization-technique implementation and integration approach. Together, they significantly alleviate the effort required for implementation of source-level memory-aware optimization techniques for Multi Processor Systems on a Chip (MPSoCs). The system-modeling approach presented in this dissertation has been located at the processor-memory-switch (PMS) abstraction level. It offers a novel combined structural and semantical description. It combines a locally-scoped, structural modeling approach, as preferred by system designers, and a fast, database-like interface, best suited for optimization technique developers. It supports model refinement and requires only limited effort for an initial abstract system model. The general structure consists of components and channels. Based on this structure, the system model provides mechanisms for database-like access to system-global target-platform properties, while requiring only definition of locally-scoped input data annotated to system-model items. A typical set of these properties contains energy-consumption and access-latency values. The request-based retrieval of system properties is a unique feature, which makes this approach superior to state-of-the-art table-lookup-based or full-system-simulation-based approaches. Combining such component-local properties to system-global target-platform data is performed via aspect handlers. These handlers define computational rules which are applied to correlated locally-scoped data along access paths in the memory-subsystem hierarchy. This approach is capable of calculating these system-global values at a rate similar to plain table lookups, while maintaining a precision close to full-system-simulation-based estimations. This has been shown for both, energy-consumption values as well as access-latency values of the MPARM platform. The MACCv2 framework provides a set of fundamental services to the optimization technique developer. On top of these services, a system model and source-code representation are provided. Further, framework-based optimization-technique implementations are encapsulated into self-contained entities exposing well-defined interfaces. This framework has been successfully used within the European Commission funded MNEMEE project. The hierarchical processing-step representation in MACCv2 allows for encapsulation of tasks at various granularity levels. For simplified reuse in future projects, the entire toolchain as well as individual optimization techniques have been represented as processing-step entities in terms of MACCv2. A common notion of target-platform structure and properties as well as inter-processing-step communication, is achieved via framework-provided services. The system-modeling approach and the framework show the right set of properties needed to support development of memory-aware optimization techniques. The MNEMEE project, continued research work, teaching activities and PhD theses have been successfully founded on approaches and the framework proposed in this dissertation

Software for Exascale Computing - SPPEXA 2016-2019

This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest

Enabling Usable and Performant Trusted Execution

A plethora of major security incidents---in which personal identifiers belonging to hundreds of millions of users were stolen---demonstrate the importance of improving the security of cloud systems. To increase security in the cloud environment, where resource sharing is the norm, we need to rethink existing approaches from the ground-up. This thesis analyzes the feasibility and security of trusted execution technologies as the cornerstone of secure software systems, to better protect users' data and privacy. Trusted Execution Environments (TEE), such as Intel SGX, has the potential to minimize the Trusted Computing Base (TCB), but they also introduce many challenges for adoption. Among these challenges are TEE's significant impact on applications' performance and non-trivial effort required to migrate legacy systems to run on these secure execution technologies. Other challenges include managing a trustworthy state across a distributed system and ensuring these individual machines are resilient to micro-architectural attacks. In this thesis, I first characterize the performance bottlenecks imposed by SGX and suggest optimization strategies. I then address two main adoption challenges for existing applications: managing permissions across a distributed system and scaling the SGX's mechanism for proving authenticity and integrity. I then analyze the resilience of trusted execution technologies to speculative execution, micro-architectural attacks, which put cloud infrastructure at risk. This analysis revealed a devastating security flaw in Intel's processors which is known as Foreshadow/L1TF. Finally, I propose a new architectural design for out-of-order processors which defeats all known speculative execution attacks.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155139/1/oweisse_1.pd

MediaSync: Handbook on Multimedia Synchronization

This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

Patterns and Pattern Languages for Mobile Augmented Reality

Mixed Reality is a relatively new field in computer science which uses technology as a medium to provide modified or enhanced views of reality or to virtually generate a new reality. Augmented Reality is a branch of Mixed Reality which blends the real-world as viewed through a computer interface with virtual objects generated by a computer. The 21st century commodification of mobile devices with multi-core Central Processing Units, Graphics Processing Units, high definition displays and multiple sensors controlled by capable Operating Systems such as Android and iOS means that Mobile Augmented Reality applications have become increasingly feasible. Mobile Augmented Reality is a multi-disciplinary field requiring a synthesis of many technologies such as computer graphics, computer vision, machine learning and mobile device programming while also requiring theoretical knowledge of diverse fields such as Linear Algebra, Projective and Differential Geometry, Probability and Optimisation. This multi-disciplinary nature has led to a fragmentation of knowledge into various specialisations, making it difficult to integrate different solution components into a coherent architecture. Software design patterns provide a solution space of tried and tested best practices for a specified problem within a given context. The solution space is non-prescriptive and is described in terms of relationships between roles that can be assigned to software components. Architectural patterns are used to specify high level designs of complete systems, as opposed to domain or tactical level patterns that address specific lower level problem areas. Pattern Languages comprise multiple software patterns combining in multiple possible sequences to form a language with the individual patterns forming the language vocabulary while the valid sequences through the patterns define the grammar. Pattern Languages provide flexible generalised solutions within a particular domain that can be customised to solve problems of differing characteristics and levels of iii complexity within the domain. The specification of one or more Pattern Languages tailored to the Mobile Augmented Reality domain can therefore provide a generalised guide for the design and architecture of Mobile Augmented Reality applications from an architectural level down to the ”nuts-and-bolts” implementation level. While there is a large body of research into the technical specialisations pertaining to Mobile Augmented Reality, there is a dearth of up-to-date literature covering Mobile Augmented Reality design. This thesis fills this vacuum by: 1. Providing architectural patterns that provide the spine on which the design of Mobile Augmented Reality artefacts can be based; 2. Documenting existing patterns within the context of Mobile Augmented Reality; 3. Identifying new patterns specific to Mobile Augmented Reality; and 4. Combining the patterns into Pattern Languages for Detection & Tracking, Rendering & Interaction and Data Access for Mobile Augmented Reality. The resulting Pattern Languages support design at multiple levels of complexity from an object-oriented framework down to specific one-off Augmented Reality applications. The practical contribution of this thesis is the specification of architectural patterns and Pattern Language that provide a unified design approach for both the overall architecture and the detailed design of Mobile Augmented Reality artefacts. The theoretical contribution is a design theory for Mobile Augmented Reality gleaned from the extraction of patterns and creation of a pattern language or languages