Portable Checkpointing for Parallel Applications

High Performance Computing (HPC) systems represent the peak of modern computational capability. As ever-increasing demands for computational power have fuelled the demand for ever-larger computing systems, modern HPC systems have grown to incorporate hundreds, thousands or as many as 130,000 processors. At these scales, the huge number of individual components in a single system makes the probability that a single component will fail quite high, with today's large HPC systems featuring mean times between failures on the order of hours or a few days. As many modern computational tasks require days or months to complete, fault tolerance becomes critical to HPC system design. The past three decades have seen significant amounts of research on parallel system fault tolerance. However, as most of it has been either theoretical or has focused on low-level solutions that are embedded into a particular operating system or type of hardware, this work has had little impact on real HPC systems. This thesis attempts to address this lack of impact by describing a high-level approach for implementing checkpoint/restart functionality that decouples the fault tolerance solution from the details of the operating system, system libraries and the hardware and instead connects it to the APIs implemented by the above components. The resulting solution enables applications that use these APIs to become self-checkpointing and self-restarting regardless of the the software/hardware platform that may implement the APIs. The particular focus of this thesis is on the problem of checkpoint/restart of parallel applications. It presents two theoretical checkpointing protocols, one for the message passing communication model and one for the shared memory model. The former is the first protocol to be compatible with application-level checkpointing of individual processes, while the latter is the first protocol that is compatible with arbitrary shared memory models, APIs, implementations and consistency protocols. These checkpointing protocols are used to implement checkpointing systems for applications that use the MPI and OpenMP parallel APIs, respectively, and are first in providing checkpoint/restart to arbitrary implementations of these popular APIs. Both checkpointing systems are extensively evaluated on multiple software/hardware platforms and are shown to feature low overheads

Replication of non-deterministic objects

This thesis discusses replication of non-deterministic objects in distributed systems to achieve fault tolerance against crash failures. The objects replicated are the virtual nodes of a distributed application. Replication is viewed as an issue that is to be dealt with only during the configuration of a distributed application and that should not affect the development of the application. Hence, replication of virtual nodes should be transparent to the application. Like all measures to achieve fault tolerance, replication introduces redundancy in the system. Not surprisingly, the main difficulty is guaranteeing the consistency of all replicas such that they behave in the same way as if the object was not replicated (replication transparency). This is further complicated if active objects (like virtual nodes) are replicated, and these objects themselves can be clients of still further objects in the distributed application. The problems of replication of active non-deterministic objects are analyzed in the context of distributed Ada 95 applications. The ISO standard for Ada 95 defines a model for distributed execution based on remote procedure calls (RPC). Virtual nodes in Ada 95 use this as their sole communication paradigm, but they may contain tasks to execute activities concurrently, thus making the execution potentially non-deterministic due to implicit timing dependencies. Such non-determinism cannot be avoided by choosing deterministic tasking policies. I present two different approaches to maintain replica consistency despite this non-determinism. In a first approach, I consider the run-time support of Ada 95 as a black box (except for the part handling remote communications). This corresponds to a non-deterministic computation model. I show that replication of non-deterministic virtual nodes requires that remote procedure calls are implemented as nested transactions. Unfortunately, effects of failures are not local to the replicas of a virtual node: when a failure occurs, nested remote calls made to other virtual nodes must be undone. Also, using transactional semantics for RPCs necessitates a compromise regarding transparency: the application must identify global state for it cannot be determined reliably in an automatic way. Further study reveals that this approach cannot be implemented in a transparent way at all because the consistency criterion of Ada 95 (linearizability) is much weaker than that of transactions (serializability). An execution of remote procedure calls as transactions may thus lead to incompatibilities with the semantics of the programming language. If remotely called subprograms on a replicated virtual node perform partial operations, i.e., entry calls on global protected objects, deadlocks that cannot be broken can occur in certain cases. Such deadlocks do not occur when the virtual node is not replicated. The transactional semantics of RPCs must therefore be exposed to the application. A second approach is based on a piecewise deterministic computation model, i.e., the execution of a virtual node is seen as a sequence of deterministic state intervals. Whenever a non-deterministic event occurs, a new state interval is started. I study replica organization under this computation model (semi-active replication). In this model, all non-deterministic decisions are made on one distinguished replica (the leader), while all other replicas (the followers) are forced to follow the same sequence of non-deterministic events. I show that it suffices to synchronize the followers with the leader upon each observable event, i.e., when the leader sends a message to some other virtual node. It is not necessary to synchronize upon each and every non-deterministic event — which would incur a prohibitively high overhead. Non-deterministic events occurring on the leader between observable events are logged and sent to the followers just before the leader executes an observable event. Consequently, it is guaranteed that the followers will reach the same state as the leader, and thus the effects of failures remain mostly local to the replicas. A prototype implementation called RAPIDS (Replicated Ada Partitions In Distributed Systems) serves as a proof of concept for this second approach, demonstrating its feasibility. RAPIDS is an Ada 95 implementation of a replication manager for semi-active replication for the GNAT development system for Ada 95. It is entirely contained within the run-time support and hence largely transparent for the application

Performance Optimization Strategies for Transactional Memory Applications

This thesis presents tools for Transactional Memory (TM) applications that cover multiple TM systems (Software, Hardware, and hybrid TM) and use information of all different layers of the TM software stack. Therefore, this thesis addresses a number of challenges to extract static information, information about the run time behavior, and expert-level knowledge to develop these new methods and strategies for the optimization of TM applications

PiCo: A Domain-Specific Language for Data Analytics Pipelines

In the world of Big Data analytics, there is a series of tools aiming at simplifying programming applications to be executed on clusters. Although each tool claims to provide better programming, data and execution models—for which only informal (and often confusing) semantics is generally provided—all share a common under- lying model, namely, the Dataflow model. Using this model as a starting point, it is possible to categorize and analyze almost all aspects about Big Data analytics tools from a high level perspective. This analysis can be considered as a first step toward a formal model to be exploited in the design of a (new) framework for Big Data analytics. By putting clear separations between all levels of abstraction (i.e., from the runtime to the user API), it is easier for a programmer or software designer to avoid mixing low level with high level aspects, as we are often used to see in state-of-the-art Big Data analytics frameworks. From the user-level perspective, we think that a clearer and simple semantics is preferable, together with a strong separation of concerns. For this reason, we use the Dataflow model as a starting point to build a programming environment with a simplified programming model implemented as a Domain-Specific Language, that is on top of a stack of layers that build a prototypical framework for Big Data analytics. The contribution of this thesis is twofold: first, we show that the proposed model is (at least) as general as existing batch and streaming frameworks (e.g., Spark, Flink, Storm, Google Dataflow), thus making it easier to understand high-level data-processing applications written in such frameworks. As result of this analysis, we provide a layered model that can represent tools and applications following the Dataflow paradigm and we show how the analyzed tools fit in each level. Second, we propose a programming environment based on such layered model in the form of a Domain-Specific Language (DSL) for processing data collections, called PiCo (Pipeline Composition). The main entity of this programming model is the Pipeline, basically a DAG-composition of processing elements. This model is intended to give the user an unique interface for both stream and batch processing, hiding completely data management and focusing only on operations, which are represented by Pipeline stages. Our DSL will be built on top of the FastFlow library, exploiting both shared and distributed parallelism, and implemented in C++11/14 with the aim of porting C++ into the Big Data world

Technology 2004, Vol. 2

Proceedings from symposia of the Technology 2004 Conference, November 8-10, 1994, Washington, DC. Volume 2 features papers on computers and software, virtual reality simulation, environmental technology, video and imaging, medical technology and life sciences, robotics and artificial intelligence, and electronics

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Undergraduate and Graduate Course Descriptions, 2007 Winter

Wright State University undergraduate and graduate course descriptions from Winter 2007

Undergraduate and Graduate Course Descriptions, 2006 Fall

Wright State University undergraduate and graduate course descriptions from Fall 2006