The University of Wyoming Computer Science Department has developed several verslo~s of a multlprogramming operating system for research and for student use. This paper describes the background of the systems and the ...
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FACOM 230-60 is a large size electronic digital computer developed by Fujitsu Limited. The system consists of 1) up to 2 processing units, 2) a 256k word (maximum) high speed core memory that operates at a 0.92 μ sec...
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Microscopic level job stream data obtained in a production environment by an event-driven software probe is used to drive a model of a multiprogramming computer system. The CPU scheduling algorithm of the model is sys...
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Microscopic level job stream data obtained in a production environment by an event-driven software probe is used to drive a model of a multiprogramming computer system. The CPU scheduling algorithm of the model is systematically varied. This technique, called trace-driven modeling, provides an accurate replica of a production environment for the testing of variations in the system. At the same time alterations in scheduling methods can be easily carried out in a controlled way with cause and effects relationships being isolated. The scheduling methods tested included the best possible and worst possible methods, the traditional methods of multiprogramming theory, round-robin, first-come-first-served, etc., and dynamic predictors. The relative and absolute performances of these scheduling methods are given. It is concluded that a successful CPU scheduling method must be preemptive and must prevent a given job from holding the CPU for too long a period.
A simple cyclic-queue model of a multiprogramming system with a fixed number of tasks is analyzed in its steady state. Expressions for queue-size distribution, average rate of job completions, and average stay-in-the-...
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A significant recent development in hybrid computation is the increasing use of multiprogramming techniques and multiprocessing hardware.1'2'3 To some extent this trend is motivated by the development of multi...
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Proposes a step-by-step approach to model the dynamic behavior and evaluate the performance of computing systems based on a technique of variable aggregation. Identification of unstable regimes of operations and criti...
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Proposes a step-by-step approach to model the dynamic behavior and evaluate the performance of computing systems based on a technique of variable aggregation. Identification of unstable regimes of operations and critical computing loads in multiprogramming paging systems; Efficiency in obtaining numerical results.
This paper deals with retrial queueing models having an unlimited/a finite orbit capacity with control retrial policy of a multiprogramming-multiprocessor computer network system. Under the Markovian assumptions and l...
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This paper deals with retrial queueing models having an unlimited/a finite orbit capacity with control retrial policy of a multiprogramming-multiprocessor computer network system. Under the Markovian assumptions and light-traffic condition, the steady-state probabilities of the number of programs in the system and the mean number of programs in the orbit are studied using matrix geometric/analytic methods. The expressions for the Laplace-Stieglitz transforms of the busy period and the waiting time are obtained. The probability generating function for the number of retrials made by a tagged program is also derived. Some interesting performance measures of the system and the various moments of quantities of interest are discussed. Finally, extensive numerical results are illustrated to reveal the impact of the system parameters on the performance measures.
As technology scales, GPUs are forecasted to incorporate an ever-increasing amount of computing resources to support thread-level parallelism. But even with the best effort, exposing massive thread-level parallelism f...
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ISBN:
(纸本)9781467389471
As technology scales, GPUs are forecasted to incorporate an ever-increasing amount of computing resources to support thread-level parallelism. But even with the best effort, exposing massive thread-level parallelism from a single GPU kernel, particularly from general purpose applications, is going to be a difficult challenge. In some cases, even if there is sufficient thread-level parallelism in a kernel, there may not be enough available memory bandwidth to support such massive concurrent thread execution. Hence, GPU resources may be underutilized as more general purpose applications are ported to execute on GPUs. In this paper, we explore multiprogramming GPUs as a way to resolve the resource underutilization issue. There is a growing hardware support for multiprogramming on GPUs. Hyper-Q has been introduced in the Kepler architecture which enables multiple kernels to be invoked via tens of hardware queue streams. Spatial multitasking has been proposed to partition GPU resources across multiple kernels. But the partitioning is done at the coarse granularity of streaming multiprocessors (SMs) where each kernel is assigned to a subset of SMs. In this paper, we advocate for partitioning a single SM across multiple kernels, which we term as intra-SM slicing. We explore various intra-SM slicing strategies that slice resources within each SM to concurrently run multiple kernels on the SM. Our results show that there is not one intra-SM slicing strategy that derives the best performance for all application pairs. We propose Warped-Slicer, a dynamic intra-SM slicing strategy that uses an analytical method for calculating the SM resource partitioning across different kernels that maximizes performance. The model relies on a set of short online profile runs to determine how each kernel's performance varies as more thread blocks from each kernel are assigned to an SM. The model takes into account the interference effect of shared resource usage across multiple kernels. The m
This paper looks at the problem of automatically tuning the database server multiprogramming level to improve database server performance under varying workloads. We describe two tuning algorithms that were considered...
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ISBN:
(纸本)9781424465217
This paper looks at the problem of automatically tuning the database server multiprogramming level to improve database server performance under varying workloads. We describe two tuning algorithms that were considered and how they performed under different workloads. We then present the hybrid approach that we have successfully implemented in SQL Anywhere 12. We found that the hybrid approach yielded better performance than each of the algorithms separately.
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