Performance Observability and Monitoring of High Performance Computing with Microservices

Traditionally, High Performance Computing (HPC) softwarehas been built and deployed as bulk-synchronous, parallel executables based on the message-passing interface (MPI) programming model. The rise of data-oriented computing paradigms and an explosion in the variety of applications that need to be supported on HPC platforms have forced a re-think of the appropriate programming and execution models to integrate this new functionality. In situ workflows demarcate a paradigm shift in HPC software development methodologies enabling a range of new applications --- from user-level data services to machine learning (ML) workflows that run alongside traditional scientific simulations. By tracing the evolution of HPC software developmentover the past 30 years, this dissertation identifies the key elements and trends responsible for the emergence of coupled, distributed, in situ workflows. This dissertation's focus is on coupled in situ workflows involving composable, high-performance microservices. After outlining the motivation to enable performance observability of these services and why existing HPC performance tools and techniques can not be applied in this context, this dissertation proposes a solution wherein a set of techniques gathers, analyzes, and orients performance data from different sources to generate observability. By leveraging microservice components initially designed to build high performance data services, this dissertation demonstrates their broader applicability for building and deploying performance monitoring and visualization as services within an in situ workflow. The results from this dissertation suggest that: (1) integration of performance data from different sources is vital to understanding the performance of service components, (2) the in situ (online) analysis of this performance data is needed to enable the adaptivity of distributed components and manage monitoring data volume, (3) statistical modeling combined with performance observations can help generate better service configurations, and (4) services are a promising architecture choice for deploying in situ performance monitoring and visualization functionality. This dissertation includes previously published and co-authored material and unpublished co-authored material

DALiuGE: A Graph Execution Framework for Harnessing the Astronomical Data Deluge

The Data Activated Liu Graph Engine - DALiuGE - is an execution framework for processing large astronomical datasets at a scale required by the Square Kilometre Array Phase 1 (SKA1). It includes an interface for expressing complex data reduction pipelines consisting of both data sets and algorithmic components and an implementation run-time to execute such pipelines on distributed resources. By mapping the logical view of a pipeline to its physical realisation, DALiuGE separates the concerns of multiple stakeholders, allowing them to collectively optimise large-scale data processing solutions in a coherent manner. The execution in DALiuGE is data-activated, where each individual data item autonomously triggers the processing on itself. Such decentralisation also makes the execution framework very scalable and flexible, supporting pipeline sizes ranging from less than ten tasks running on a laptop to tens of millions of concurrent tasks on the second fastest supercomputer in the world. DALiuGE has been used in production for reducing interferometry data sets from the Karl E. Jansky Very Large Array and the Mingantu Ultrawide Spectral Radioheliograph; and is being developed as the execution framework prototype for the Science Data Processor (SDP) consortium of the Square Kilometre Array (SKA) telescope. This paper presents a technical overview of DALiuGE and discusses case studies from the CHILES and MUSER projects that use DALiuGE to execute production pipelines. In a companion paper, we provide in-depth analysis of DALiuGE's scalability to very large numbers of tasks on two supercomputing facilities.Comment: 31 pages, 12 figures, currently under review by Astronomy and Computin

Belle II Technical Design Report

The Belle detector at the KEKB electron-positron collider has collected almost 1 billion Y(4S) events in its decade of operation. Super-KEKB, an upgrade of KEKB is under construction, to increase the luminosity by two orders of magnitude during a three-year shutdown, with an ultimate goal of 8E35 /cm^2 /s luminosity. To exploit the increased luminosity, an upgrade of the Belle detector has been proposed. A new international collaboration Belle-II, is being formed. The Technical Design Report presents physics motivation, basic methods of the accelerator upgrade, as well as key improvements of the detector.Comment: Edited by: Z. Dole\v{z}al and S. Un

An Interactive Distributed Simulation Framework With Application To Wireless Networks And Intrusion Detection

In this dissertation, we describe the portable, open-source distributed simulation framework (WINDS) targeting simulations of wireless network infrastructures that we have developed. We present the simulation framework which uses modular architecture and apply the framework to studies of mobility pattern effects, routing and intrusion detection mechanisms in simulations of large-scale wireless ad hoc, infrastructure, and totally mobile networks. The distributed simulations within the framework execute seamlessly and transparently to the user on a symmetric multiprocessor cluster computer or a network of computers with no modifications to the code or user objects. A visual graphical interface precisely depicts simulation object states and interactions throughout the simulation execution, giving the user full control over the simulation in real time. The network configuration is detected by the framework, and communication latency is taken into consideration when dynamically adjusting the simulation clock, allowing the simulation to run on a heterogeneous computing system. The simulation framework is easily extensible to multi-cluster systems and computing grids. An entire simulation system can be constructed in a short time, utilizing user-created and supplied simulation components, including mobile nodes, base stations, routing algorithms, traffic patterns and other objects. These objects are automatically compiled and loaded by the simulation system, and are available for dynamic simulation injection at runtime. Using our distributed simulation framework, we have studied modern intrusion detection systems (IDS) and assessed applicability of existing intrusion detection techniques to wireless networks. We have developed a mobile agent-based IDS targeting mobile wireless networks, and introduced load-balancing optimizations aimed at limited-resource systems to improve intrusion detection performance. Packet-based monitoring agents of our IDS employ a CASE-based reasoner engine that performs fast lookups of network packets in the existing SNORT-based intrusion rule-set. Experiments were performed using the intrusion data from MIT Lincoln Laboratories studies, and executed on a cluster computer utilizing our distributed simulation system

Novel Operation Modes of Accelerated Neuromorphic Hardware

The hybrid operation mode relies on a combination of conventional computing resources and a neuromorphic, beyond von Neumann system to perform a joint real-time experiment. The interactive operation mode provides prompt feedback to the user and benefits from high experiment throughput. The performance of a custom transport-layer protocol is evaluated connecting the accelerated neuromorphic system and the computer cluster. Wire-speed performance is achieved between host and eight FPGAs ((846.7 ± 1.2) MiB/s, 94% wire speed), and between two hosts using 10-Gigabit Ethernet (> 99%) as well as 40GbE (> 99%) to explore scaling behavior. The software architecture to process neuronal network experiments at high rates is presented including measurements which address the key performance indicators. During hybrid operation, the tight coupling between both resources requires low-latency communication. Using a custom-developed software framework, an average one-way latency between two host computers connected via 10GbE is found to be (2.4 ± 0.2) μs and (8.5 ± 0.4) μs to the neuromorphic system. A hybrid experiment is designed to demonstrate the hardware infrastructure and software framework. Starting from a conventional neuronal network simulation, the experiment is gradually migrated into a time-continuous experiment which interacts between a host computer and the neuromorphic system in real time. Results of the intermediate steps and the final, hybrid operation are evaluated

Fault-tolerant dynamic parallel schedules

Dynamic Parallel Schedules (DPS) is a high-level framework for developing parallel applications on distributed memory computers such as clusters of PCs. DPS applications are defined by using directed acyclic flow graphs composed of user-defined operations. These operations derive from basic concepts provided by the framework: split, merge, leaf and stream operations. Whereas a simple parallel application can be expressed with a split-leaf-merge sequence of operations, flow graphs of arbitrary complexity can be created. DPS provides run-time support for dynamically mapping flow graph operations onto the nodes of a cluster. The flow graph based application description used in DPS allows the framework to offer many additional features, most of these transparently to the application developer. In order to maximize performance, DPS applications benefit from automatic overlapping of computations and communications and from implicit pipelining. The framework provides simple primitives for flow control and load balancing. Applications can integrate flow graph parts provided by other applications as parallel components. Since the mapping of DPS applications to processing nodes can be dynamically changed at runtime, DPS provides a basis for developing malleable applications. The DPS framework provides a complete fault tolerance mechanism based on the dynamic mapping capabilities, ensuring continued execution of parallel applications even in the presence of multiple node failures. DPS is provided as an open-source, cross-platform C++ library allowing DPS applications and services to run on heterogeneous clusters

Master/worker parallel discrete event simulation

The execution of parallel discrete event simulation across metacomputing infrastructures is examined. A master/worker architecture for parallel discrete event simulation is proposed providing robust executions under a dynamic set of services with system-level support for fault tolerance, semi-automated client-directed load balancing, portability across heterogeneous machines, and the ability to run codes on idle or time-sharing clients without significant interaction by users. Research questions and challenges associated with issues and limitations with the work distribution paradigm, targeted computational domain, performance metrics, and the intended class of applications to be used in this context are analyzed and discussed. A portable web services approach to master/worker parallel discrete event simulation is proposed and evaluated with subsequent optimizations to increase the efficiency of large-scale simulation execution through distributed master service design and intrinsic overhead reduction. New techniques for addressing challenges associated with optimistic parallel discrete event simulation across metacomputing such as rollbacks and message unsending with an inherently different computation paradigm utilizing master services and time windows are proposed and examined. Results indicate that a master/worker approach utilizing loosely coupled resources is a viable means for high throughput parallel discrete event simulation by enhancing existing computational capacity or providing alternate execution capability for less time-critical codes.Ph.D.Committee Chair: Fujimoto, Richard; Committee Member: Bader, David; Committee Member: Perumalla, Kalyan; Committee Member: Riley, George; Committee Member: Vuduc, Richar

Service-Oriented Ad Hoc Grid Computing

Subject of this thesis are the design and implementation of an ad hoc Grid infrastructure. The vision of an ad hoc Grid further evolves conventional service-oriented Grid systems into a more robust, more flexible and more usable environment that is still standards compliant and interoperable with other Grid systems. A lot of work in current Grid middleware systems is focused on providing transparent access to high performance computing (HPC) resources (e.g. clusters) in virtual organizations spanning multiple institutions. The ad hoc Grid vision presented in this thesis exceeds this view in combining classical Grid components with more flexible components and usage models, allowing to form an environment combining dedicated HPC-resources with a large number of personal computers forming a "Desktop Grid". Three examples from medical research, media research and mechanical engineering are presented as application scenarios for a service-oriented ad hoc Grid infrastructure. These sample applications are also used to derive requirements for the runtime environment as well as development tools for such an ad hoc Grid environment. These requirements form the basis for the design and implementation of the Marburg ad hoc Grid Environment (MAGE) and the Grid Development Tools for Eclipse (GDT). MAGE is an implementation of a WSRF-compliant Grid middleware, that satisfies the criteria for an ad hoc Grid middleware presented in the introduction to this thesis. GDT extends the popular Eclipse integrated development environment by components that support application development both for traditional service-oriented Grid middleware systems as well as ad hoc Grid infrastructures such as MAGE. These development tools represent the first fully model driven approach to Grid service development integrated with infrastructure management components in service-oriented Grid computing. This thesis is concluded by a quantitative discussion of the performance overhead imposed by the presented extensions to a service-oriented Grid middleware as well as a discussion of the qualitative improvements gained by the overall solution. The conclusion of this thesis also gives an outlook on future developments and areas for further research. One of these qualitative improvements is "hot deployment" the ability to install and remove Grid services in a running node without interrupt to other active services on the same node. Hot deployment has been introduced as a novelty in service-oriented Grid systems as a result of the research conducted for this thesis. It extends service-oriented Grid computing with a new paradigm, making installation of individual application components a functional aspect of the application. This thesis further explores the idea of using peer-to-peer (P2P networking for Grid computing by combining a general purpose P2P framework with a standard compliant Grid middleware. In previous work the application of P2P systems has been limited to replica location and use of P2P index structures for discovery purposes. The work presented in this thesis also uses P2P networking to realize seamless communication accross network barriers. Even though the web service standards have been designed for the internet, the two-way communication requirement introduced by the WSRF-standards and particularly the notification pattern is not well supported by the web service standards. This defficiency can be answered by mechanisms that are part of such general purpose P2P communication frameworks. Existing security infrastructures for Grid systems focus on protection of data during transmission and access control to individual resources or the overall Grid environment. This thesis focuses on security issues within a single node of a dynamically changing service-oriented Grid environment. To counter the security threads arising from the new capabilities of an ad hoc Grid, a number of novel isolation solutions are presented. These solutions address security issues and isolation on a fine-grained level providing a range of applicable basic mechanisms for isolation, ranging from lightweight system call interposition to complete para-virtualization of the operating systems

Partial replication in distributed software transactional memory

Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaDistributed software transactional memory (DSTM) is emerging as an interesting alternative for distributed concurrency control. Usually, DSTM systems resort to data distribution and full replication techniques in order to provide scalability and fault tolerance. Nevertheless, distribution does not provide support for fault tolerance and full replication limits the system’s total storage capacity. In this context, partial data replication rises as an intermediate solution that combines the best of the previous two trying to mitigate their disadvantages. This strategy has been explored by the distributed databases research field, but has been little addressed in the context of transactional memory and, to the best of our knowledge, it has never before been incorporated into a DSTM system for a general-purpose programming language. Thus, we defend the claim that it is possible to combine both full and partial data replication in such systems. Accordingly, we developed a prototype of a DSTM system combining full and partial data replication for Java programs. We built from an existent DSTM framework and extended it with support for partial data replication. With the proposed framework, we implemented a partially replicated DSTM. We evaluated the proposed system using known benchmarks, and the evaluation showcases the existence of scenarios where partial data replication can be advantageous, e.g., in scenarios with small amounts of transactions modifying fully replicated data. The results of this thesis show that we were able to sustain our claim by implementing a prototype that effectively combines full and partial data replication in a DSTM system. The modularity of the presented framework allows the easy implementation of its various components, and it provides a non-intrusive interface to applications.Fundação para a Ciência e Tecnologia - (FCT/MCTES) in the scope of the research project PTDC/EIA-EIA/113613/2009 (Synergy-VM

An Autonomic Cross-Platform Operating Environment for On-Demand Internet Computing

The Internet has evolved into a global and ubiquitous communication medium interconnecting powerful application servers, diverse desktop computers and mobile notebooks. Along with recent developments in computer technology, such as the convergence of computing and communication devices, the way how people use computers and the Internet has changed people´s working habits and has led to new application scenarios. On the one hand, pervasive computing, ubiquitous computing and nomadic computing become more and more important since different computing devices like PDAs and notebooks may be used concurrently and alternately, e.g. while the user is on the move. On the other hand, the ubiquitous availability and pervasive interconnection of computing systems have fostered various trends towards the dynamic utilization and spontaneous collaboration of available remote computing resources, which are addressed by approaches like utility computing, grid computing, cloud computing and public computing. From a general point of view, the common objective of this development is the use of Internet applications on demand, i.e. applications that are not installed in advance by a platform administrator but are dynamically deployed and run as they are requested by the application user. The heterogeneous and unmanaged nature of the Internet represents a major challenge for the on demand use of custom Internet applications across heterogeneous hardware platforms, operating systems and network environments. Promising remedies are autonomic computing systems that are supposed to maintain themselves without particular user or application intervention. In this thesis, an Autonomic Cross-Platform Operating Environment (ACOE) is presented that supports On Demand Internet Computing (ODIC), such as dynamic application composition and ad hoc execution migration. The approach is based on an integration middleware called crossware that does not replace existing middleware but operates as a self-managing mediator between diverse application requirements and heterogeneous platform configurations. A Java implementation of the Crossware Development Kit (XDK) is presented, followed by the description of the On Demand Internet Computing System (ODIX). The feasibility of the approach is shown by the implementation of an Internet Application Workbench, an Internet Application Factory and an Internet Peer Federation. They illustrate the use of ODIX to support local, remote and distributed ODIC, respectively. Finally, the suitability of the approach is discussed with respect to the support of ODIC