Reading list of selected PASM-related publications

Prepared for a chapter to be published in the forthcoming Encyclopedia of Parallel Computing by Springer Publishing Company. The Encyclopedia will contain a broad coverage of the field and will include entries on machine organization, programming, algorithms, and applications. The broad coverage, together with extensive pointers to the literature for in-depth study, is expected to make the Encyclopedia a useful reference tool in parallel computing

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Models and heuristics for robust resource allocation in parallel and distributed computing systems

Includes bibliographical references.This is an overview of the robust resource allocation research efforts that have been and continue to be conducted by the CSU Robustness in Computer Systems Group. Parallel and distributed computing systems, consisting of a (usually heterogeneous) set of machines and networks, frequently operate in environments where delivered performance degrades due to unpredictable circumstances. Such unpredictability can be the result of sudden machine failures, increases in system load, or errors caused by inaccurate initial estimation. The research into developing models and heuristics for parallel and distributed computing systems that create robust resource allocations is presented.This research was supported by NSF under grant No. CNS-0615170 and by the Colorado State University George T. Abell Endowment

Robustness of resource allocation in parallel and distributed computing systems, The

Includes bibliographical references (page [9]).This paper gives an overview of the material to be discussed in the invited keynote presentation by H. J. Siegel; it summarizes our research in [1]. Performing computing and communication tasks on parallel and distributed systems involves the coordinated use of different types of machines, networks, interfaces, and other resources. Decisions about how best to allocate resources are often based on estimated values of task and system parameters, due to uncertainties in the system environment. An important research problem is the development of resource management strategies that can guarantee a particular system performance given such uncertainties. We have designed a methodology for deriving the degree of robustness of a resource allocation - the maximum amount of collective uncertainty in system parameters within which a user-specified level of system performance (QoS) can be guaranteed. Our four-step procedure for deriving a robustness metric for an arbitrary system will be presented. We will illustrate this procedure and its usefulness by deriving robustness metrics for some example distributed systems

Measuring robustness for distributed computing systems

Includes bibliographical references (page 6).Performing computing and communication tasks on parallel and distributed systems may involve the coordinated use of different types of machines, networks, interfaces, and other resources. All of these resources should be allocated in a way that maximizes some system performance measure. However, allocation decisions and performance prediction are often based on "nominal" values of application and system parameters. The actual values of these parameters may differ from the nominal ones, e.g., because of inaccuracies in the initial estimation or because of changes over time caused by an unpredictable system environment. An important question then arises: given a system design, what extent of departure from the assumed circumstances will cause the performance to be unacceptably degraded? That is, how robust is the system? To address this issue, one needs to derive a design methodology for deriving the degree of robustness of a resource allocation - the maximum amount of collective uncertainty in application and system parameters within which a user specified level of performance can be guaranteed. Our procedure for this is presented in this paper. The main contributions of this research are (1) a mathematical description of a metric for the robustness of a resource allocation with respect to desired system performance features against multiple perturbations in multiple system and environmental conditions, (2) a procedure for deriving a robustness metric for an arbitrary system, and (3) example applications of this procedure to several different systems

The Robustness of Resource Allocation in Parallel and Distributed Computing Systems

This paper gives an overview of the material to be discussed in the invited keynote presentation by H. J. Siegel. Performing computing and communication tasks on parallel and distributed systems involves the coordinated use of different types of machines, networks, interfaces, and other resources. Decisions about how best to allocate resources are often based on estimated values of task and system parameters, due to uncertainties in the system environment. An important research problem is the development of resource management strategies that can guarantee a particular system performance given such uncertainties. We have designed a methodology for deriving the degree of robustness of a resource allocation - the maximum amount of collective uncertainty in system parameters within which a user-specified level of system performance (QoS) can be guaranteed. Our four-step procedure for deriving a robustness metric for an arbitrary system will be presented. We will illustrate this procedure and its usefulness by deriving robustness metrics for some example distributed systems

Destination Tag Routing Techniques Based on a State Model for the IADM Network

A state model is proposed for solving the problem of routing and rerouting messages in the Inverse Augmented Data Manipulator (IADM) network. Using this model, necessary and sufficient conditions for the reroutability of messages are established, and then destination tag schemes are derived. These schemes are simpler, more efficient and require less complex hardware than previously proposed routing schemes. Two destination tag schemes are proposed. For one of the schemes, rerouting is totally transparent to the sender of the message and any blocked link of a given type can be avoided. Compared with previous works that deal with the same type of blockage, the timeXspace complexity is reduced from O(logN) to O(1). For the other scheme, rerouting is possible for any type of link blockage. A universal rerouting algorithm is constructed based on the second scheme, which finds a blockage-free path for any combination of multiple blockages if there exists such a path, and indicates absence of such a path if there exists none. In addition, the state model is used to derive constructively a lower bound on the number of subgraphs which are isomorphic to the Indirect Binary N-Cube network in the IADM network. This knowledge can be used to characterize properties of the IADM networks and for permutation routing in the IADM networks

Exploiting concurrency among tasks in partitionable parallel processing systems

Includes bibliographical references.One benefit of partitionable parallel processing systems is their ability to execute multiple independent tasks simultaneously. Previous work has identified conditions such that, when there are k tasks to be processed, partitioning the system such that all k tasks are processed simultaneously results in a minimum overall execution time. An alternate condition is developed that provides additional insight into the effects of parallelism on execution time. This result, and previous results, however, assume that execution times are data independent. It will be shown that data-dependent tasks do not necessarily execute faster when processed simultaneously even if the condition is met. A model is developed that provides for the possible variability of a task's execution time and is used in a new framework to study the problem of finding an optimal mapping for identical, independent data-dependent execution time tasks onto partitionable systems. Extension of this framework to situations where the k tasks are non-identical is discussed.This work was supported by the Naval Ocean Systems Center under the High Performance Computing Block, ONT, and by the Office of Naval Research under grant number N00014-90-J-1937

Parallel algorithm for singular value decomposition as applied to failure tolerant manipulators, A

Includes bibliographical references (pages [348-349]).The system of equations that govern kinematically redundant manipulators is commonly solved by finding the singular value decomposition (SVD) of the corresponding Jacobian matrix. This can require considerable amounts of time to compute, thus a parallel SVD algorithm minimizing execution time is sought. The approach employed here lends itself to parallelization by using Givens rotations and information from previous decompositions. The key contributions of this research include the presentation and implementation of a new variation of a parallel SVD algorithm to compute the SVD for a set of post-fault Jacobians. Results from implementation of the algorithm on a MasPar MP-1 and an IBM SP2 are provided. Specific issues considered for each implementation include how data is mapped to the processing elements, the effect that increasing the number of processing elements has on execution time, and the type of parallel architecture used

Experimental Evaluation of SIMD PE-Mask Generation and Hybrid Mode Parallel Computing on Multi- Microprocessor Systems

Experimentation aimed at determining the potential efficiency of multi-microprocessor designs of SIMD machines is reported. The experimentation is based on timing measurements made on the PASM system prototype at Purdue. The application used to measure and evaluate this phenomenon was bitonic sorting, which has feasible solutions in both SIMD and MIMD modes of computation, as well as in at least two hybrids of SlMD and MIMD modes. Bitonic sorting was coded in these four ways and experiments were performed that examine the tradeoffs among all of these modes. Also, a new PE mask generation scheme for multiple of-the-shelf microprocessor based SIMD systems is proposed, and its performance was measured