Native structure-based modeling and simulation of biomolecular systems per mouse click

Background Molecular dynamics (MD) simulations provide valuable insight into biomolecular systems at the atomic level. Notwithstanding the ever-increasing power of high performance computers current MD simulations face several challenges: the fastest atomic movements require time steps of a few femtoseconds which are small compared to biomolecular relevant timescales of milliseconds or even seconds for large conformational motions. At the same time, scalability to a large number of cores is limited mostly due to long-range interactions. An appealing alternative to atomic-level simulations is coarse-graining the resolution of the system or reducing the complexity of the Hamiltonian to improve sampling while decreasing computational costs. Native structure-based models, also called Gō-type models, are based on energy landscape theory and the principle of minimal frustration. They have been tremendously successful in explaining fundamental questions of, e.g., protein folding, RNA folding or protein function. At the same time, they are computationally sufficiently inexpensive to run complex simulations on smaller computing systems or even commodity hardware. Still, their setup and evaluation is quite complex even though sophisticated software packages support their realization. Results Here, we establish an efficient infrastructure for native structure-based models to support the community and enable high-throughput simulations on remote computing resources via GridBeans and UNICORE middleware. This infrastructure organizes the setup of such simulations resulting in increased comparability of simulation results. At the same time, complete workflows for advanced simulation protocols can be established and managed on remote resources by a graphical interface which increases reusability of protocols and additionally lowers the entry barrier into such simulations for, e.g., experimental scientists who want to compare their results against simulations. We demonstrate the power of this approach by illustrating it for protein folding simulations for a range of proteins. Conclusions We present software enhancing the entire workflow for native structure-based simulations including exception-handling and evaluations. Extending the capability and improving the accessibility of existing simulation packages the software goes beyond the state of the art in the domain of biomolecular simulations. Thus we expect that it will stimulate more individuals from the community to employ more confidently modeling in their research

Programação dataflow de aplicações de fluxo de dados contínuo para sistemas heterogêneos

Stream processing applications have high-demanding performance requirements that are hard to tackle using traditional parallel models on modern many-core architectures, such as GPUs. On the other hand, recent dataflow computing models can naturally exploit parallelism for a wide class of applications. This work presents an extension to an existing dataflow library for Java. The library extension implements high-level constructs with multiple command queues to enable the superposition of memory operations and kernel executions on GPUs. Experimental results show that significant speedup can be achieved for a subset of well-known stream processing applications: Volume Ray-Casting, Path-Tracing and Sobel Filter.Aplicações stream possuem demandam rigorosos requisitos de performance que são difíceis de serem atingidos utilizando modelos paralelos tradicionais em arquiteturas many-cores como GPUs. Por outro lado, os recentes modelos de computação Dataflow podem naturalmente explorar paralelismo em uma abrangente classe de aplicações. Este trabalho apresenta uma extensão para uma biblioteca Dataflow em Java. Esta extensão implementa construções em alto nível com múltiplas filas de comando que permitem a sobreposição de operações de memória e execução de kernel em GPUs. Os resultados deste trabalho mostraram que um significante speedup pode ser atingido para um conjunto de aplicações bem conhecidas de processamento stream como: Ray-Casting, Path-Tracing e filtro Sobel

Uma adaptação do escalonador estático da biblioteca dataflow sucuri para computação in-situ

In the dataflow computation model, instructions or tasks are executed according to data dependencies, instead of following program order, thus allowing parallelism to be exposed naturally. Sucuri is a dataflow library for Python that allows each user to specify their application as a dependency graph and execute it transparently in clusters of multicores, while taking care of scheduling issues. Recent trends in Fog and In-situ computing assume that storage and network devices will be equipped with processing elements that usually have lower power consumption and performance. An important decision for such systems is whether to move data to traditional processors (paying the communication costs), or to perform the computation where the data sits, using a potentially slower processor. Hence, runtime environments that deal with that trade-off are of extreme importance. This work presents a study on different factors that should be considered when running dataflow applications in a In-situ environment. We use Sucuri to manage the execution in a small system with a regular PC and a Parallella board, emulating a smart storage, and a set of experiments was performed to show how data transfer size, network latency, packet loss rates and computational complexity affect execution time when outsourcing computation to the smart storage. Then, a static scheduling solution is presented, allowing Sucuri to take the best decision where to execute the application, avoiding outsourcing when there would be no performance gains.No modelo de computação por fluxo de dados, dataflow, as instruções ou tarefas são executadas de acordo com as dependências de dados, ao invés de seguir a ordem do programa, permitindo a exploração natural de paralelismo. A Sucuri é uma biblioteca dataflow em Python que permite aos usuários especificarem suas aplicações como um grafo de dependências, e as executa de maneira transparente em clusters de multicores, enquanto se encarrega também dos problemas de escalonamento. Avan¸cos recentes em computação fog e in-situ assumem que dispositivos de armazenamento e de rede serão equipados com unidades de processamento, geralmente de baixo consumo de energia e baixo desempenho. Uma decisão importante em tais sistemas é a de migrar os dados para os processadores tradicionais, pagando os custos de comunicação, ou realizar a computação onde o dado está (in-situ), usando um processador de desempenho potencialmente menor. Este trabalho apresenta um estudo dos diferentes fatores que devem ser levados em consideração quando executando aplicações dataflow em um ambiente de computação in-situ. A Sucuri foi utilizada para gerenciar a execução em um pequeno sistema composto de um computador comum e uma placa Parallella simulando um disco inteligente, e uma série de experimentos foi realizada para mostrar como o tamanho dos dados a serem transferidos, a latência de rede, a perda de pacotes e a complexidade computacional da aplicação afetam o tempo de execução quando o processamento é deixado a cargo desse disco. Então, uma solução de escalonamento estático que leva em conta tais fatores é apresentada, dando a Sucuri poder de decisão sobre onde melhor realizar o processamento dos dados, evitando fazer a computação in-situ quando a mesma não trouxer ganhos de performance

Isolates, channels, and event streams for composable distributed programming

The actor model has been a model of choice for building reliable distributed systems. On one hand, it ensures that message-processing is serialized within each actor, preserving the familiar sequential programming model. On the other hand, programs written in the actor model are location-transparent. The model is sufficiently low-level to express arbitrary message protocols. Composing these protocols is the key to high-level abstractions. Unfortunately, it is difficult to reuse or compose message protocols with actors. Reactive isolates, proposed in this paper, simplify protocol composition with first-class typed channels and event streams. We compare reactive isolates and the actor model on concrete programs. We identify obstacles for composition in the classic actor model, and show how to overcome them. We then show how to build reusable, composable distributed computing components in the new model

Anpassen verteilter eingebetteter Anwendungen im laufenden Betrieb

The availability of third-party apps is among the key success factors for software ecosystems: The users benefit from more features and innovation speed, while third-party solution vendors can leverage the platform to create successful offerings. However, this requires a certain decoupling of engineering activities of the different parties not achieved for distributed control systems, yet. While late and dynamic integration of third-party components would be required, resulting control systems must provide high reliability regarding real-time requirements, which leads to integration complexity. Closing this gap would particularly contribute to the vision of software-defined manufacturing, where an ecosystem of modern IT-based control system components could lead to faster innovations due to their higher abstraction and availability of various frameworks. Therefore, this thesis addresses the research question: How we can use modern IT technologies and enable independent evolution and easy third-party integration of software components in distributed control systems, where deterministic end-to-end reactivity is required, and especially, how can we apply distributed changes to such systems consistently and reactively during operation? This thesis describes the challenges and related approaches in detail and points out that existing approaches do not fully address our research question. To tackle this gap, a formal specification of a runtime platform concept is presented in conjunction with a model-based engineering approach. The engineering approach decouples the engineering steps of component definition, integration, and deployment. The runtime platform supports this approach by isolating the components, while still offering predictable end-to-end real-time behavior. Independent evolution of software components is supported through a concept for synchronous reconfiguration during full operation, i.e., dynamic orchestration of components. Time-critical state transfer is supported, too, and can lead to bounded quality degradation, at most. The reconfiguration planning is supported by analysis concepts, including simulation of a formally specified system and reconfiguration, and analyzing potential quality degradation with the evolving dataflow graph (EDFG) method. A platform-specific realization of the concepts, the real-time container architecture, is described as a reference implementation. The model and the prototype are evaluated regarding their feasibility and applicability of the concepts by two case studies. The first case study is a minimalistic distributed control system used in different setups with different component variants and reconfiguration plans to compare the model and the prototype and to gather runtime statistics. The second case study is a smart factory showcase system with more challenging application components and interface technologies. The conclusion is that the concepts are feasible and applicable, even though the concepts and the prototype still need to be worked on in future -- for example, to reach shorter cycle times.Eine große Auswahl von Drittanbieter-Lösungen ist einer der Schlüsselfaktoren für Software Ecosystems: Nutzer profitieren vom breiten Angebot und schnellen Innovationen, während Drittanbieter über die Plattform erfolgreiche Lösungen anbieten können. Das jedoch setzt eine gewisse Entkopplung von Entwicklungsschritten der Beteiligten voraus, welche für verteilte Steuerungssysteme noch nicht erreicht wurde. Während Drittanbieter-Komponenten möglichst spät -- sogar Laufzeit -- integriert werden müssten, müssen Steuerungssysteme jedoch eine hohe Zuverlässigkeit gegenüber Echtzeitanforderungen aufweisen, was zu Integrationskomplexität führt. Dies zu lösen würde insbesondere zur Vision von Software-definierter Produktion beitragen, da ein Ecosystem für moderne IT-basierte Steuerungskomponenten wegen deren höherem Abstraktionsgrad und der Vielzahl verfügbarer Frameworks zu schnellerer Innovation führen würde. Daher behandelt diese Dissertation folgende Forschungsfrage: Wie können wir moderne IT-Technologien verwenden und unabhängige Entwicklung und einfache Integration von Software-Komponenten in verteilten Steuerungssystemen ermöglichen, wo Ende-zu-Ende-Echtzeitverhalten gefordert ist, und wie können wir insbesondere verteilte Änderungen an solchen Systemen konsistent und im Vollbetrieb vornehmen? Diese Dissertation beschreibt Herausforderungen und verwandte Ansätze im Detail und zeigt auf, dass existierende Ansätze diese Frage nicht vollständig behandeln. Um diese Lücke zu schließen, beschreiben wir eine formale Spezifikation einer Laufzeit-Plattform und einen zugehörigen Modell-basierten Engineering-Ansatz. Dieser Ansatz entkoppelt die Design-Schritte der Entwicklung, Integration und des Deployments von Komponenten. Die Laufzeit-Plattform unterstützt den Ansatz durch Isolation von Komponenten und zugleich Zeit-deterministischem Ende-zu-Ende-Verhalten. Unabhängige Entwicklung und Integration werden durch Konzepte für synchrone Rekonfiguration im Vollbetrieb unterstützt, also durch dynamische Orchestrierung. Dies beinhaltet auch Zeit-kritische Zustands-Transfers mit höchstens begrenzter Qualitätsminderung, wenn überhaupt. Rekonfigurationsplanung wird durch Analysekonzepte unterstützt, einschließlich der Simulation formal spezifizierter Systeme und Rekonfigurationen und der Analyse der etwaigen Qualitätsminderung mit dem Evolving Dataflow Graph (EDFG). Die Real-Time Container Architecture wird als Referenzimplementierung und Evaluationsplattform beschrieben. Zwei Fallstudien untersuchen Machbarkeit und Nützlichkeit der Konzepte. Die erste verwendet verschiedene Varianten und Rekonfigurationen eines minimalistischen verteilten Steuerungssystems, um Modell und Prototyp zu vergleichen sowie Laufzeitstatistiken zu erheben. Die zweite Fallstudie ist ein Smart-Factory-Demonstrator, welcher herausforderndere Applikationskomponenten und Schnittstellentechnologien verwendet. Die Konzepte sind den Studien nach machbar und nützlich, auch wenn sowohl die Konzepte als auch der Prototyp noch weitere Arbeit benötigen -- zum Beispiel, um kürzere Zyklen zu erreichen

Mapping Cross-Cloud Systems: Challenges and Opportunities

Abstract Recent years have seen significant growth in the cloud computing market, both in terms of provider competition (including private offerings) and customer adoption. However, the cloud computing world still lacks adopted standard programming interfaces, which has a knock-on effect on the costs associated with interoperability and severely limits the flexibility and portability of applications and virtual infrastructures. This has brought about an increasing number of cross-cloud architectures, i.e. systems that span across cloud provisioning boundaries. This paper condenses discussions from the CrossCloud event series to outline the types of cross-cloud systems and their associated design decisions, and laments challenges and opportunities they create

An FPGA implementation of an investigative many-core processor, Fynbos : in support of a Fortran autoparallelising software pipeline

Includes bibliographical references.In light of the power, memory, ILP, and utilisation walls facing the computing industry, this work examines the hypothetical many-core approach to finding greater compute performance and efficiency. In order to achieve greater efficiency in an environment in which Moore’s law continues but TDP has been capped, a means of deriving performance from dark and dim silicon is needed. The many-core hypothesis is one approach to exploiting these available transistors efficiently. As understood in this work, it involves trading in hardware control complexity for hundreds to thousands of parallel simple processing elements, and operating at a clock speed sufficiently low as to allow the efficiency gains of near threshold voltage operation. Performance is there- fore dependant on exploiting a new degree of fine-grained parallelism such as is currently only found in GPGPUs, but in a manner that is not as restrictive in application domain range. While removing the complex control hardware of traditional CPUs provides space for more arithmetic hardware, a basic level of control is still required. For a number of reasons this work chooses to replace this control largely with static scheduling. This pushes the burden of control primarily to the software and specifically the compiler, rather not to the programmer or to an application specific means of control simplification. An existing legacy tool chain capable of autoparallelising sequential Fortran code to the degree of parallelism necessary for many-core exists. This work implements a many-core architecture to match it. Prototyping the design on an FPGA, it is possible to examine the real world performance of the compiler-architecture system to a greater degree than simulation only would allow. Comparing theoretical peak performance and real performance in a case study application, the system is found to be more efficient than any other reviewed, but to also significantly under perform relative to current competing architectures. This failing is apportioned to taking the need for simple hardware too far, and an inability to implement static scheduling mitigating tactics due to lack of support for such in the compiler