This paper describes the high-level execution and communication support provided in JGrid, a service-oriented dynamic grid framework. One of its core services, the compute service, is the key component in creating dyn...
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ISBN:
(纸本)9781424400546
This paper describes the high-level execution and communication support provided in JGrid, a service-oriented dynamic grid framework. One of its core services, the compute service, is the key component in creating dynamic computational grid systems that enable the execution of sequential and parallel interactive grid applications. A fundamental set of program execution modes supported by the service is described, then a programming model and its corresponding application programming interface is presented. The execution support of the service architecture is described in detail illustrating how remote evaluation and run-time task spawning are provided. The paper also shows in detail how task spawning and dynamic proxies can be used for a service-oriented communication mechanism for coarse-grain parallel grid applications
We develop an efficient linear programming detector (LPD) for multiple-input multiple-output (MIMO) systems. Instead of using the usual l 2 norm, our proposed LPD uses the l 1 norm as the detection metric, resulting...
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We develop an efficient linear programming detector (LPD) for multiple-input multiple-output (MIMO) systems. Instead of using the usual l 2 norm, our proposed LPD uses the l 1 norm as the detection metric, resulting in a mixed-integer linear program (MILP). Two branch-and-bound algorithms are proposed to solve the MILP. The solution of the MILP achieves the same full diversity order as the maximum likelihood detector. The MILP is further relaxed to a linear program (LP), which can be readily solved using the standard simplex method. We show that in some cases the solution of the LP is guaranteed to be that of the MILP. The LPD is also extended to the joint detection and decoding of linear block coded MIMO systems. Our LPD can be immediately implemented using mature circuits design for the simplex algorithm
Provides an abstract of the keynote presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings.
Provides an abstract of the keynote presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings.
As low-cost multiprocessing reaches a wider market, a greater number of programmers will need to be trained for parallel programming. Current studies exploring usability engineering for parallel programming focus only...
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As low-cost multiprocessing reaches a wider market, a greater number of programmers will need to be trained for parallel programming. Current studies exploring usability engineering for parallel programming focus only on experienced parallel programmers. This paper applies the card sorting method used in psychology research to understanding the software needs of the novice parallel programmer. This paper demonstrates that novices organize parallel problems by domain type whereas experts use parallel communication type.
Polyvariant specialization allows generating multiple versions of a procedure, which can then be separately optimized for different uses. Since allowing a high degree of polyvariance often results in more optimized co...
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ISBN:
(纸本)3540326545
Polyvariant specialization allows generating multiple versions of a procedure, which can then be separately optimized for different uses. Since allowing a high degree of polyvariance often results in more optimized code, polyvariant specializers, such as most partial evaluators, can generate a large number of versions. This can produce unnecessarily large residual programs. Also, large programs can be slower due to cache miss effects. A possible solution to this problem is to introduce a minimization step which identifies sets of equivalent versions, and replace all occurrences of such versions by a single one. In this work we present a unifying view of the problem of superfluous polyvariance. It includes both partial deduction and abstract multiple specialization. As regards partial deduction, we extend existing approaches in several ways. First, previous work has dealt with pure logic programs and a very limited class of builtins. Herein we propose an extension to traditional characteristic trees which can be used in the presence of calls to external predicates. This includes all builtins, libraries, other user modules, etc. Second, we propose the possibility of collapsing versions which are not strictly equivalent. This allows trading time for space and can be useful in the context of embedded and pervasive systems. This is done by residualizing certain computations for external predicates which would otherwise be performed at specialization time. Third, we provide an experimental evaluation of the potential gains achievable using minimization which leads to interesting conclusions.
This contribution describes an automatic technique for detecting maximal domains of attraction for nonlinear systems using genetic programming (GP). The theoretical basis for the work is Lyapunov's direct method, ...
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This contribution describes an automatic technique for detecting maximal domains of attraction for nonlinear systems using genetic programming (GP). The theoretical basis for the work is Lyapunov's direct method, which provides sufficient conditions for the existence of a region of attraction of a stable focus. In work presented here, our GP approach for defining Lyapunov functions that accurately predict the maximum region of attraction has been extended by defining a target function accounting for level sets. We demonstrate the approach on the analysis of two dynamic systems: (a) van der Pol's equation, which features both a stable and unstable limit cycle; and (b) a model of an exothermic, continuous stirred tank reactor (CSTR), whose stable trajectories tend to move away from the origin before converging
This paper studies the optimal least squares (LS) and minimax design of hybrid filter bank analog to digital converters (HFB ADCs) using second order cone programming (SOCP). The resulting problem is convex and it all...
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This paper studies the optimal least squares (LS) and minimax design of hybrid filter bank analog to digital converters (HFB ADCs) using second order cone programming (SOCP). The resulting problem is convex and it allows linear and quadratic constraints such as prescribed signal reconstruction magnitude flatness and aliasing canceling error to be incorporated. Two new robust HFB ADC design algorithms based on stochastic uncertainty and worst-case uncertainty models are also proposed. Design results show that the SOCP approach offers more flexibility than conventional methods and the robust design algorithms are more robust to parameter uncertainties than the SOCP design when the uncertainties are not taken into account
Design and experimental evaluation of power-balanced reconfigurable floating-gate-MOS logic circuit is presented. The circuit can represent all 512 symmetric Boolean functions for eight inputs and 256 Boolean function...
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Design and experimental evaluation of power-balanced reconfigurable floating-gate-MOS logic circuit is presented. The circuit can represent all 512 symmetric Boolean functions for eight inputs and 256 Boolean functions for three-input symmetric/asymmetric functions. The programming of function is done by control signals. Namely, no change in hardware configuration is required. The proposed circuit employs a highly symmetric architecture. The input data and the control signals are broadcasted in pairs with their complementary values. As a result, the power consumption of the circuit is independent of the input data and the logic function. Hence, the proposed circuit is resistant to the power analysis attack
For linear continuous-time scalar systems, the paper proposes the problem of synthesizing a minimum-time rest-to-rest feedforward control with input and output constraints. In a behavioral framework, simple sufficient...
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For linear continuous-time scalar systems, the paper proposes the problem of synthesizing a minimum-time rest-to-rest feedforward control with input and output constraints. In a behavioral framework, simple sufficient conditions for the problem to have a solution are provided. Then using discretization, an arbitrarily good approximation to the global minimum-time solution is found by solving a sequence of linear programming problems. Computational examples to show the effectiveness of the proposed approach are included
A form of routing based on an analogy with geometrical optics has recently been proposed for use in wireless networks with a very large number of nodes. The analogy hinges on taking a macroscopic view of the network, ...
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A form of routing based on an analogy with geometrical optics has recently been proposed for use in wireless networks with a very large number of nodes. The analogy hinges on taking a macroscopic view of the network, and describing it solely in terms of a cost function, that is analogous to the refractive index of optics. In this setting, optimal routes resemble rays of light propagating through a properly defined optical medium. This method has intuitive appeal and leads to insightful results; nevertheless many issues remain unresolved. Two of these issues are treated here. First, we discuss the problem of route discovery, also considering the challenging cases where the optimal routes starting from a given node intersect themselves, and also fail to cover the whole network in a reasonable manner. Then, we show how optical routing can be derived using dynamic programming. The derivation illuminates the connection between this form of routing and traditional routing algorithms that are also based on dynamic programming.
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