Preparing for Exascale: Modeling MPI for Many-Core Systems using Fine-Grain Queues.
Abstract not provided.
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HAVOQGT is a C++ framework that can be used to create highly parallel graph traversal algorithms. The framework stores the graph and algorithmic data structures on external memory that is typically mapped to high performance locally attached NAND FLASH arrays. The framework supports a vertex-centered visitor programming model. The frameworkd has been used to implement breadth first search, connected components, and single source shortest path.
At signalized intersections, vehicle speed profile plays a vital role in determining fuel consumption and emissions. With advances of connected and automated vehicle technology, vehicles are able to receive predicted traffic information from the infrastructure in real-time to plan their trajectories in a fuel-efficient way. In this paper, an eco-driving model is developed for hybrid electric vehicles in a congested urban traffic environment. The vehicle queuing process is explicitly modeled by the shockwave profile model with consideration of vehicle deceleration and acceleration to provide a green window for eco-vehicle trajectory planning. A trigonometric speed profile is applied to minimize fuel consumption and maximize driving comfort with a low jerk. A hybrid electric vehicle fuel consumption model is built and calibrated with real vehicle data to evaluate the energy benefit of the eco-vehicles. Simulation results from a real-world corridor of six intersections show that the proposed eco-driving model can significantly reduce energy consumption by 8.7% on average and by 23.5% at maximum, without sacrificing mobility.
A modified Poisson arrival, infinite server queuing model is used to determine the effects of limiting the number of broadcast channels (C) of a direct broadcast satellite used for public service purposes (remote health care, education, etc.). The model is based on the reproductive property of the Poisson distribution. A difference equation has been developed to describe the change in the Poisson parameter. When all initially delayed arrivals reenter the system a (C plus 1) order polynomial must be solved to determine the effective value of the Poisson parameter. When less than 100% of the arrivals reenter the system the effective value must be determined by solving a transcendental equation. The model was used to determine the minimum number of channels required for a disaster warning satellite without degradation in performance. Results predicted by the queuing model were compared with the results of digital simulation.
Some codes for arbitration of priorities among subsystem computers or peripheral device controllers connected to a parallel data bus are described. At arbitration time, several subsystems present wire-OR, parallel code words to the bus, and the central computer can identify the subsystem of highest priority and determine which of two or more transmission services the subsystem requires. A mathematical discussion of the optimality of the codes with regard to the number of subsystems that may participate in the scheme for a given number of wires is presented along with the number of services that each subsystem may request.
Synchronous time division multiplexing is analyzed. Packets of information arrive at the system as a compound Poisson process, and are transmitted only during individual periodic intervals. Packet arrivals are blocked (lost) if the system has a finite capacity and is congested. Using the theory of semiregenerative processes, the distribution of the number of packets in the system (system size) is found. This nonstationary distribution is used to determine the complete system behavior, including the delay distributions, the blocking probability, and the density of the system size at arrival instants. Numerical examples illustrate applications of the results given.
A logical classification of multiprocessor structures from the point of view of control applications is presented. A computation of the response time distribution for a canonical model of a real time multiprocessor is presented. The multiprocessor is approximated by a blocking model. Two separate models are derived: one created from the system's point of view, and the other from the point of view of an incoming task.
Two communication traffic streams with Poisson statistics arrive at a network node. These are to be transmitted across a channel with a total bandwidth capacity of C slots. Messages not accepted at the node are assumed to be lost. Under the assumptions of exponential service time distributions, the problem of dynamic allocation of available channel bandwidth among the two traffic types is studied in order to minimize a weighted sum of blocking probabilities. Modeling the system as a two-dimensional Markov chain is studied to minimize a weighted sum of blocking probabilities. Modeling the system as a two-dimensional Markov chain, it is shown by an application of dynamic programming principles that the optimal policy has the form of a 'switching curve'.
The designers of networks of computers must assess the capacity of the network to complete work within reasonable times. The utilization law, Little's law, forced-flow law, and response time formula are simple tools that can be used to calculate throughput and response times of networks. Bottleneck analysis can be used to calculate simple lower bounds on response time in terms of individual server parameters and the load on network as a whole. These simple results are important tools for all users of scientific networks - back of the envelope calculations can quickly reveal the effects of distant servers on local throughput and response time.
Queuing systems are considered where the waiting or sojourn times of customers are constrained by specified deadlines. A performance measure of interest in these systems is the probability that a customer exceeds its assigned deadline. A new class of gradient estimators is presented for such performance measures with respect to various system parameters. The approach is applicable to a general class of problems and is based on efficiently capturing sensitivity information for probabilities of event occurrences from observed sample paths.
Several buffer structures are discussed and compared in terms of implementation complexity, interswitch handshaking requirements, and their ability to deal with variations in traffic patterns and message lengths. A new design of buffers is presented that provide non-FIFO message handling and efficient storage allocation for variable size packets using linked lists managed by a simple on-chip controller. The new buffer design is evaluated by comparing it to several alternative designs in the context of a multistage interconnection network. The present modeling and simulations show that the new buffer outperforms alternative buffers and can thus be used to improve the performance of a wide variety of systems currently using less efficient buffers.
The authors consider an M/G/1 queuing with a time-varying arrival rate. The objective is to obtain infinitesimal perturbation analysis (IPA) gradient estimates for various performance measures of interest with respect to certain system parameters. In particular, the authors consider the mean system time over n arrivals and an arrival rate alternating between two values. By choosing a convenient sample path representation of this system, they derive an unbiased IPA gradient estimator which, however, is not consistent, and investigate the nature of this problem.
In message passing implementations, associative matching structures are used to permit list entries to be searched in parallel fashion, thereby avoiding the delay of linear list traversal. List management capabilities are provided to support list entry turnover semantics and priority ordering semantics.
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