Compositional schedulability analysis of real-time actor-based systems

We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checke

Characterization of Parallel Application Runtime Sensitivity on Multi-core High Performance Computing Systems

A commonly seen behavior of parallel applications is that their runtime is influenced by network communication load. The way a parallel application is run in a network and the presence of other applications and processes in the network can contribute to a wide range of variations in the runtime. Therefore, in order to achieve consistent and optimal runtimes, it is important to understand and characterize the runtime sensitivity of parallel applications with respect to execution under the presence of network communication load. In this research, runtime sensitivities for various parallel applications were studied by applying additional network communication load. In particular, the focus was on the runtime sensitivity of parallel applications on a multi-core multi-processor (MCMP) system where less network switching and routing are involved compared to single-core single-processor machines. The objective of this work was to determine if a previously developed sensitivity model for single-core single-processor machines still holds good for multi-core machines. For this purpose, previously developed tools (PACE and PARSE) were used to perturb the communication sub-system while executing several parallel application benchmarks such as the NAS benchmarks and PSTSWM. Runtime variations of these parallel applications were studied, under a specific network communication load, for different test cases by changing computing core allocation. A 10-node 80-core cluster was used as the test bed for this research purpose. Several test cases were explored using a variety of core allocations (process locations) for the application under test (AUT) to simulate job scheduler fragmentation. To ensure statistical significance, several iterations (trial runs) were executed in each test case. Results indicate that the idea of application sensitivity to communication sub-system performance degradation holds for MCMP architectures

Automated Cluster-Based Web Service Performance Tuning

In this paper, we apply the Active Harmony system to improve the performance of a cluster-based web service system. The performance improvement cannot easily be achieved by tuning individual components for such a system. The experimental results show that there is no single configuration for the system that performs well for all kinds of workloads. By tuning the parameters, the Active Harmony helps the system adapt to different workloads and improve the performance up to 16%. For scalability, we demonstrate how to reduce the time when tuning a large system with many tunable parameters. Finally an algorithm is proposed to automatically adjust the structure of cluster-based web systems, and the system throughput is improved up to 70% using this technology. (UMIACS-TR-2003-84

A Policy-Based Resource Brokering Environment for Computational Grids

With the advances in networking infrastructure in general, and the Internet in particular, we can build grid environments that allow users to utilize a diverse set of distributed and heterogeneous resources. Since the focus of such environments is the efficient usage of the underlying resources, a critical component is the resource brokering environment that mediates the discovery, access and usage of these resources. With the consumer\u27s constraints, provider\u27s rules, distributed heterogeneous resources and the large number of scheduling choices, the resource brokering environment needs to decide where to place the user\u27s jobs and when to start their execution in a way that yields the best performance for the user and the best utilization for the resource provider. As brokering and scheduling are very complicated tasks, most current resource brokering environments are either specific to a particular grid environment or have limited features. This makes them unsuitable for large applications with heterogeneous requirements. In addition, most of these resource brokering environments lack flexibility. Policies at the resource-, application-, and system-levels cannot be specified and enforced to provide commitment to the guaranteed level of allocation that can help in attracting grid users and contribute to establishing credibility for existing grid environments. In this thesis, we propose and prototype a flexible and extensible Policy-based Resource Brokering Environment (PROBE) that can be utilized by various grid systems. In designing PROBE, we follow a policy-based approach that provides PROBE with the intelligence to not only match the user\u27s request with the right set of resources, but also to assure the guaranteed level of the allocation. PROBE looks at the task allocation as a Service Level Agreement (SLA) that needs to be enforced between the resource provider and the resource consumer. The policy-based framework is useful in a typical grid environment where resources, most of the time, are not dedicated. In implementing PROBE, we have utilized a layered architecture and façade design patterns. These along with the well-defined API, make the framework independent of any architecture and allow for the incorporation of different types of scheduling algorithms, applications and platform adaptors as the underlying environment requires. We have utilized XML as a base for all the specification needs. This provides a flexible mechanism to specify the heterogeneous resources and user\u27s requests along with their allocation constraints. We have developed XML-based specifications by which high-level internal structures of resources, jobs and policies can be specified. This provides interoperability in which a grid system can utilize PROBE to discover and use resources controlled by other grid systems. We have implemented a prototype of PROBE to demonstrate its feasibility. We also describe a test bed environment and the evaluation experiments that we have conducted to demonstrate the usefulness and effectiveness of our approach

Towards Automatic Performance Tuning

When the computing environment becomes heterogeneous and applications become modular with reusable components, automatic performance tuning is needed for these applications to run well in different environments. We present the Active Harmony automated runtime tuning system and describe the interface used by programs to make applications tunable. We present the optimization algorithm used to adjust application parameters and the Library Specification Layer which helps program library developers expose multiple variations of the same API using different algorithms. By comparing the experience stored in a database, the tuning server is able to find appropriate configurations more rapidly. Utilizing historical data together with a mechanism that estimates performance speeds up the tuning process. To avoid performance oscillations during the initial phase of the tuning process, we use improved search refinement techniques that use configurations equally spaced throughout the performance search space to make the tuning process smoother. We also introduce a parameter prioritizing tool to focus on those performance critical parameters. We demonstrate how to reduce the time when tuning a large system with many tunable parameters. The search space can be reduced by checking the relations among parameters to avoid unnecessary search. In addition, for homogeneous processing nodes, we demonstrate how to use one set of the parameters and replicate the values to the remaining processing nodes. For environments where parameters can be divided into independent groups, an individual tuning server is used for each group. An algorithm is given to automatically adjust the structure of cluster-based web systems and it improves the system throughput up to 70%. We successfully apply the Active Harmony system to a cluster-based web service system and scientific programs. By tuning the parameters, Active Harmony helps the system adapt to different workloads and improve the performance up to 16%. The performance improvement cannot easily be achieved by tuning individual components for such a system and there is no single configuration that performs well for all kinds of workloads. All the design and experimental results show that Active Harmony is a feasible and useful tool in performance tuning