Programming Models
Stochastic Programming Models in Financial Optimization: A Survey 1
... A potential problem for stochastic programming models in financial optimization are arbi- trage opportunities in the event tree that are due to approximation errors. Klaassen (1997)[59] was the first to ...
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Enhancing the interoperability between distributed-memory and task-based programming models
... To the best of our knowledge, this is the first approach which aims to develop an interoperability mechanism for the GASPI and shared-memory programming models. The usual parallelization strategy in hybrid ...
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Interpolating Value Functions in Discrete Choice Dynamic Programming Models
... dynamic programming models have been shown to be a valuable tool for analyzing a wide range of economic ...these models is the compu- tational burden associated with computing the high dimensional ...
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Improving the interoperability between MPI and task-based programming models
... The MPI Standard guarantees that point–to–point commu- nications among two ranks are always ordered as long as these leverage the same tag and communicator. However, when multiple threads communicate simultaneously, the ...
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Survey on Pure Parallel Programming Models: OpenMP and MPI
... ABSTRACT: This paper presents all pure parallel programming models. shared and distributed memory approaches are also reviewed in this paper. This paper introduces the contribution of Open standards such as ...
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On algorithmic reductions in task-parallel programming models
... task-parallel programming models that support the expression of data-flows in the ...task-parallel programming models is discussed in Chapter ...
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A hardware runtime for task-based programming models
... Several papers deal with hardware support for task de- pendence management. Intel CARBON [19], Asynchronous Direct Messages (ADM) [20] and Task Scheduling Unit [21] introduced hierarchy hardware queue architectures to ...
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Programming models to support data science workflows
... other models go one step further by generalising the Skeleton model and allow- ing users to define Directed Acyclic Graph (DAG) of ...Skeleton models, DAG models allow application developers to ...
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Programming Models for Parallel Heterogeneous Computing
... introduces the concept of streams. The OpenCL API is more low level than CUDA. Powerful programming models and APIs like CUDA and OpenCL allow time efficient reformulation of multi-threaded code for CPUs ...
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Nexus#: a distributed hardware task manager for task-based programming models
... based programming models allow exploring paral- lelism in the application with minimal modifications through the use of various ...based programming models such as StarSs [14], and OmpSs ...
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Parallel Brownian dynamics simulations with the message-passing and PGAS programming models
... Brownian dynamics simulations are nowadays used to perform many stud- ies in different areas of physics and biology [1], and there are several software tools that help implementing these simulations, such as BrownDye [2] ...
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The usefulness and efficacy of linear programming models as farm management tools
... Describing a grazing system as a set of mathematical equations is not an easy task, and the diagrammatic representation of a grazed livestock production system (Figure 1) prepared by the GSL model developers (Anderson ...
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Waste processing facility location problem by stochastic programming: Models and solutions
... Existing modeling and solution challenges are related to the fact that the studied problems often combine deterministic and stochastic parameters to- gether with nonlinear terms and both continuous and discrete decision ...
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Programming Models for Technical Computing on Clouds and Supercomputers (aka HPC)
... High Throughput Computing; pleasingly parallel; grid applications Multiple users long tail of science and usages parameter searches Internet of Things Sensor nets as in cloud support of [r] ...
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Sequential Bounding Methods for Stochastic Programming Models of Production Planning.
... belonging to the corresponding set. Such algorithms can be adapted to a sequential approxi- mation scheme, where the approximate problem is iteratively solved and modified by refining the partition of the support for the ...
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Programming Models for Reconfigurable Application Accelerators
... memory models, any processing element can theoretically make direct hardware memory references into the global address space without requiring knowledge of whether the memory location that it is reading from or ...
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Stochastic Programming Models for Appointment Scheduling that Compensate for Variation in Server Behavior.
... three models which examine the effect of three different behaviors: learning, fatigue, and congestion ...created models that determine service time based on the current state of customers in the ...
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A practitioner's guide to Bayesian estimation of discrete choice dynamic programming models
... choice models, making the posterior mean an attractive estimator compared with classical point estimates in that setting (Albert and Chib 1993; McCulloch and Rossi 1994; Allenby and Lenk 1994; Allenby 1994; Rossi ...
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Special Classes of Fuzzy Integer Programming Models with All-different Constraints
... integer programming problem with all-dierent constraints involving fuzzy random variables can be converted to the integer programming model with a single-objective ...large-scale models, the proposed ...
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Linking Programming models between Grids, Web 2 0 and Multicore
... The three major models are supported by HPCS languages which are very interesting but too monolithic So the Fine grain thread parallelism and Large Scale loosely synchronous data paralle[r] ...
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