An Open-Source, extensible spacecraft simulation and modeling (Open-SESSAME) framework was developed with the aim of providing to researchers the ability to quickly test satellite algorithms while allowing them the ability to view and extend the underlying code. The software is distributed under the GPL (General Public License) and the package's extensibility allows users to implement their own components into the libraries, investigate new algorithms, or tie in existing software or hardware components for algorithm and flight component testing. This thesis presents the purpose behind the development of the framework, the software design architecture and implementation, and a roadmap of the future for the software package. / Master of Science

The proliferation of a diverse set of heterogeneous computing platforms in conjunction with the plethora of programming languages and optimization techniques on each language for each underlying architecture exacerbate widespread adoption of such platforms. This is especially true for novice programmers and the non-technical-savvy masses that are largely precluded from enjoying the advantages of high-performance computing. Moreover, different groups within the heterogeneous computing community (e.g., hardware architects, tool developers, and programmers) are presented with new challenges with respect to performance, programmability, and portability (or the three P's) of heterogeneous computing. In this work we discuss such challenges and identify benchmarking techniques based on computation and communication patterns as an appropriate means for the systematic evaluation of heterogeneous computing with respect to the three P's. Our proposed approach is based on OpenCL implementations of the Berkeley dwarfs. We use our benchmark suite (OpenDwarfs) in characterizing performance of state-of-the-art parallel architectures, and as the main component of a methodology (Telescoping Architectures) for identifying trends in future heterogeneous architectures. Furthermore, we employ OpenDwarfs in a multi-faceted study on the gaps between the three P's in the context of the modern heterogeneous computing landscape. Our case-study spans a variety of compilers, languages, optimizations, and target architectures, including the CPU, GPU, MIC, and FPGA. Based on our insights, and extending aspects of prior research (e.g., in compilers, programming languages, and auto-tuning), we propose the introduction of grid-based data structures as the basis of programming frameworks and present a prototype unified framework (GLAF) that encompasses a novel visual programming environment with code generation, auto-parallelization, and auto-tuning capabilities. Our results, which span scientific domains, indicate that our holistic approach constitutes a viable alternative towards enhancing the three P's and further democratizing heterogeneous, parallel computing for non-programming-savvy audiences, and especially domain scientists. / Ph. D. / In the past decade computing has moved from <i>single-core</i> machines, that is machines with a CPU that can execute code in a serial manner, to <i>multi-core</i> ones, i.e., machines with CPUs that can execute code in a parallel fashion. Another paradigm shift that has manifested in the past years entails computing that utilizes <i>heterogeneous processing</i>, as opposed to <i>homogeneous processing</i>. In the latter case a single type of processor (CPU) is responsible for executing a given program, whereas in the former case different types of processors (such as CPUs, graphics processors or other accelerators) collaborate in an effort to tackle computationally difficult problems in a fast, parallel manner. The shift to <i>multi-core, parallel, heterogeneous computing</i> described above is accompanied by an associated shift in programming languages for such platforms, as well as techniques to optimize programs for high performance (i.e., execution speed). The unique complexities of parallel and heterogeneous computing exacerbate widespread adoption of such platforms. This is especially true for novice programmers and the non-technical-savvy masses that are largely precluded from the advantages of high-performance computing. Challenges include obtaining fast execution speeds (i.e., <i>performance<i>), easiness of programming (i.e., <i>programmability</i>), and the ability to execute programs across different heterogeneous platforms (i.e., <i>portability</i>). Performance, programmability, and portability constitute the <i>3 P’s of heterogeneous computing</i>. In this work we discuss the above challenges in detail and provide insights and solutions for different interest groups within the computing community, such as computer architects, tool developers and programmers. We propose an approach for evaluating existing heterogeneous computing platforms based on the concept of <i>dwarf-based benchmarks</i> (i.e., applications that are characterized by certain computation and communication patterns). Furthermore, we propose a methodology for utilizing the dwarf concept for evaluating potential future heterogeneous platforms. In our research we attempt to quantify the trade-offs between performance, programmability, and portability in a wide set of modern heterogeneous platforms. Based on the above, we seek to bridge the 3 P’s by introducing a programming framework that democratizes parallel algorithm development on heterogeneous architectures for novice programmers and domain scientists. Specifically, our framework produces parallel, optimized code implementations in multiple languages with the potential of executing across different heterogeneous platforms.

Les applications ubiquitaires évoluent dans des environnements plus hétérogènes et plus dynamiques que ceux des systèmes distribués traditionnels. La criticité des domaines applicatifs impliqués et la vocation non intrusive de l'informatique ubiquitaire exigent de garantir la robustesse des applications avant et pendant leur déploiement en situation réelle. Les solutions proposant de gérer la dynamicité des environnements ubiquitaires offrent des canevas de programmation dont la généricité ne permet pas de garantir la fiabilité des applications développées. D'autres solutions permettent davantage de vérifications en assurant, par exemple, l'intégrité des communications. Cependant, ces vérifications, telles que proposées dans ces solutions, empêchent la prise en compte de la dynamicité, indispensable à la mise en oeuvre d'applications ubiquitaires. Dans cette thèse, nous proposons un canevas logiciel visant à concevoir, développer, vérifier et tester les applications ubiquitaires avant leur déploiement en environnements réels. Notre approche repose sur des spécifications haut niveau des applications cibles. Chaque spécification, écrites dans le langage DIASPEC, est analysée, vérifiée et compilée par le compilateur DIASPEC qui génère un canevas logiciel dédié, incluant un canevas de programmation et un canevas de simulation. Les canevas de programmation générés fournissent du support pour la programmation d'applications ubiquitaires. Ils garantissent l'intégrité des communications tout en permettant la gestion de la dynamicité des environnements ubiquitaires. Les canevas de simulation générés fournissent du support pour le test des applications ainsi développées. Les contributions de cette thèse sont les suivantes ; Nous proposons l'approche DIAGEN qui permet, à partir de spécifications d'architectures logicielles ubiquitaires, de générer du support de programmation et un ensemble de vérifications dédiés au développement d'applications ubiquitaires. Ces spécifications reposent sur un langage déclaratif, appelé DIASPEC, qui permet de décrire les types de services composant les applications ubiquitaires cibles. Le compilateur DIASPEC vérifie la cohérence des spécifications et génère, à partir de celles-ci, des canevas de programmation dédiés. Les canevas de programmation générés garantissent l'intégrité des communications d'applications dynamiques. Nous avons développé DIASIM, un simulateur pour tester à l'exécution, le comportement des applications développées avec l'approche DIAGEN. DIASIM permet de tester les applications sans les modifier et d'intégrer incrémentalement des services réels dans les scénarios de simulation. Nous avons montré que l'approche DIAGEN permet davantage de vérifications statiques tout en gérant la dynamicité des environnements ubiquitaires et en permettant une plus grande concision des applications développées. Nous avons analysé les canevas de programmation générés pour la gestion de réunion, l'immotique et la téléphonie. / Ubiquitous systems have to cope with more heterogeneous and more dynamic environments than traditional distributed systems. The criticity of application domains related to ubiquitous computing requires to ensure the robustness of applications before their deployment in actual situations. Some approaches handle the dynamicity of ubiquitous environments but propose generic programming frameworks. This genericity is a major obstacle for producing robust applications. Other approaches enable more verifications that ensure, for example, communication integrity. However, as performed by these approaches, these verifications are not compatible with managing constant changes of ubiquitous environments. This thesis proposes a declarative approach to generate software frameworks for ubiquitous computing. Our approach relies on high-level specifications of target applications. These specifications, written in the DIASPEC language, are analyzed, checked and compiled by the DIASPEC compiler which generates dedicated software frameworks, including programming frameworks and simulation frameworks. The generated programming frameworks provide programming support for developing ubiquitous applications while the generated simulation frameworks provide testing support for these applications. Programming frameworks ensure communication integrity while handling the dynamicity of ubiquitous environments. Furthermore, they are generated on top of a generic middleware; the layered architecture of this middleware allows ubiquitous applications to be independent of underlying technologies. The contributions of this thesis are as follows; We present the DIAGEN approach which proposes to generate, from specifications of ubiquitous software architectures, programming support and verifications dedicated to the development of ubiquitous applications. These specifications are written in a declarative language, called DIASPEC, which allows to describe all service types composing the target ubiquitous applications. The DIASPEC compiler checks the specification consistency and generates dedicated programming frameworks. These programming frameworks ensure communication integrity of dynamic applications. The underlying middleware has a layered architecture, making programming frameworks independent of software buses. Thus, applications are portable without modification. We present the DIASIM simulator that tests, at run time, the behavior of applications developed with DIAGEN. DIASIM allows to test applications without modification and to incrementally integrate actual services in simulation scenarios. We show that DIAGEN applications are more concise than existing approaches while enabling more verifications and handling the dynamicity of ubiquitous environments.

SkePU (Skeleton Programming Framework for Multi-core CPU and Multi-GPU Systems) is a parallel computing framework developed by Johan Enmyren and Christoph Kessler at Linköpings Universitet. This C++ template library provides a simple and unified interface for specifying data-parallel computations with the help of skeletons and is targeted to multiple backends e.g. for a sequential CPU, parallel CPUs using MPI and OpenMP or GPUs using CUDA and OpenCL. SkePU is comprised of seven data-parallel skeletons and one task-parallel skeleton and these skeletons use two types of containers: vector and matrix to model real-life parallel applications. In this thesis, we address the extension of the SkePU framework by extending the matrix container (which stores 2-D data values) that can efficiently use the existing skeletons to develop parallel scientific applications on large-scale clusters using MPI. This piece of work focuses on the distribution of the matrix among the participating processes which after receiving their share of data can execute the application in parallel. This work covers all of the seven data-parallel skeletons. Each skeleton has been tested with a small application program. In addition to measurement of performance improvement from the application program’s execution time, we have also done a communication cost analysis for all skeletons with MPI using the LogGP model. In order to evaluate and test the operational efficiency of the extension, we have considered a PDE solver application. Through this application, we have demonstrated the performance gain and scalability of the extended framework. The performance improvement was more when computational load dominates the memory I/O operations. The results show that using the extension can serve as a viable approach while implementing real-life parallel applications on large-scale clusters.