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We consider single commodity strictly convex network flow problems. The dual problem is unconstrained, differentiable and well suited for solution via parallel iterative methods. We propose and prove convergence of parallel asynchronous modified Newton algorithms for solving the dual problem. Parallel asynchronous Newton multisplitting algorithms are also considered, their convergence is also shown...
We propose a novel sparse matrix partitioning scheme, called semi-two-dimensional (s2D), for efficient parallelization of sparse matrix-vector multiply (SpMV) operations on distributed memory systems. In s2D, matrix nonzeros are more flexibly distributed among processors than one dimensional (row wise or column wise) partitioning schemes. Yet, there is a constraint which renders s2D less flexible...
Constraints imposed by power delivery and costs will be key design impediments to the development of next generation High-Performance Computing (HPC) systems. To remedy these impediments, solutions that impose power bounds (or caps) on over-provisioned computing systems to remain within the physical (and financial) power limits have been proposed. Uninformed power capping can significantly impact...
As we move towards the Exactable era of supercomputing, node-level failures are becoming more common-place, frequent check pointing is currently used to recover from such failures in long-running science applications. While compute performance has steadily improved year-on-year, parallel I/O performance has stalled, meaning check pointing is fast becoming a bottleneck to performance. Using current...
Computing platforms are consuming more and more energy due to the increasing number of nodes composing them. To minimize the operating costs of these platforms many techniques have been used. Dynamic voltage and frequency scaling (DVFS) is one of them. It reduces the frequency of a CPU to lower its energy consumption. However, lowering the frequency of a CPU may increase the execution time of an application...
Several approaches to reduce the power consumption of data enters have been described in the literature, most of which aim to improve energy efficiency by trading off performance for reducing power consumption. However, these approaches do not always provide means for administrators and users to specify how they want to explore such trade-offs. This work provides techniques for assigning jobs to distributed...
The paper explores use of various partitioning methods to store RDF data effectively, to meet the needs of extensively growing highly interactive semantic web applications. It proposes a combinational approach of structure index partitioning and vertical partitioning -- SIVP and demonstrates the implementation of SIVP. The paper presents five metrics to measure and analyze performance of SIVP store...
With the advent of large high volume data, we have seen need for real time analytic techniques like Complex Event Processing. This paper extends a Complex Event Processing Engine to support real time identification of technical chart patterns from streaming data. Technical chart patterns are known interesting recurring patterns on time series data, and they are used by experts in time series data...
Modern field-programmable gate arrays (FPGAs) allow runtime partial reconfiguration (PR) of the FPGA, enabling PR benefits such as runtime adaptability and extensibility, and reduces the application's area requirement. However, PR application development requires non-traditional expertise and lengthy design time effort. Since high-level synthesis (HLS) languages afford fast application development...
Interdependent cyber-physical systems (CPS) connect physical resources between independently motivated actors who seek to maximize profits while providing physical services to consumers. Cyber attacks in seemingly distant parts of these systems have local consequences, and techniques are needed to analyze and optimize defensive costs in the face of increasing cyber threats. This paper presents a technique...
Computing Voronoi tessellations in an arbitrary number of dimensions is a computationally difficult task. This problem becomes exacerbated in distributed environments, such as Peer-to-Peer networks and Wireless networks, where Voronoi tessellations have useful applications. We present our Distributed Greedy Voronoi Heuristic, which approximates Voronoi tessellations in distributed environments. Our...
The ability to automatically detect faults or fault patterns to enhance system reliability is important for system administrators in reducing system failures. To achieve this objective, the message logs from cluster system are augmented with failure information, i.e., The raw log data is labelled. However, tagging or labelling of raw log data is very costly. In this paper, our objective is to detect...
Collective operations are widely used in large scale scientific applications, and critical to the scalability of these applications for large process counts. It has also been demonstrated that collective operations have to be carefully tuned for a given platform and application scenario to maximize their performance. Non-blocking collective operations extend the concept of collective operations by...
Efficient utilization of high-performance computing (HPC) platforms is an important and complex problem. Execution models, abstract descriptions of the dynamic runtime behavior of the execution stack, have significant impact on the utilization of HPC systems. Using a computational chemistry kernel as a case study and a wide variety of execution models combined with load balancing techniques, we explore...
Runtime loop optimization and speculative execution are becoming more and more prominent to leverage performance in the current multi-core and many-core era. However, a wider and more efficient use of such techniques is mainly hampered by the prohibitive time overhead induced by centralized data race detection, dynamic code behavior modeling and code generation. Most of the existing Thread Level Speculation...
Many applications in network analysis require the computation of the network's laplacian pseudo-inverse - e.g., Topological centrality in social networks or estimating commute times in electrical networks. As large graphs become ubiquitous, the traditional approaches - with quadratic or cubic complexity in the number of vertices - do not scale. To alleviate this performance issue, a divide-and-conquer...
We present in this paper a general framework to study issues of effective load balancing and scheduling in highly parallel and distributed environments such as currently built Cloud computing systems. We propose a novel approach based on the concept of the Sandpile cellular automaton: a decentralized multi-agent system working in a critical state at the edge of chaos. Our goal is providing fairness...
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