Existing approaches for creating infrastructure performance models require manual coding of these experiments, or ignore the detailed properties in the models.
When we want to deliver the result we have to add the contents of the cache into the accumulator.
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User Assignment and Movement Prediction in Wireless Networks.
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The main idea is to augment the long accumulator with cache information.
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Ginpex provides a metamodel for experiment specification and comes with predefined experiment templates that provide automated experiment execution on the target platform and also automate the evaluation of the experiment results.
Hence, we provide at least two units per operation.
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Modern data centers are subject to an increasing demand for flexibility.
We tested the functionality, correctness and performance for both implementations in a case study for vector and matrix operations.
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Our primary intention is to give an easily understandable specification of hardware for interval arithmetic.
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The article is devoted to the problem of mobility and resource management in heterogeneous wireless networks.
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Interval arithmetic, as it is standardized by the IEEE working group P1788 can be implemented by using floating point arithmetic units with directed rounding modes.
In this paper we discuss the interaction of expression templates with OpenCL devices.
We tested the functionality, correctness and performance of a prototype in different case studies for floating point as well as interval data types and compared it against other implementations.
However, building performance models manually requires a lot of time and effort.
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Proceedings of the 3rd International Symposium on Business Modeling and Software Design (BMSD 2013), Noordwijkerhout, The Netherlands, 2013.
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We evaluate Ginpex using three case studies, where experiments are executed to quantify various infrastructure properties.
We will improve the handling of the rounding mode switches using expression templates and show how the constructed expression trees can be combined with other features like automatic differentiation.
Performance Modeling and Prediction of Virtualized Storage Systems.
The development of the tool started in 2003 and since then the tool has been distributed to more than 120 organizations worldwide.
By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages.
This tutorial presents an introduction to queueing Petri nets first introducing the modeling formalism itself and then summarizing the results of several modeling case studies which demonstrate how queueing Petri nets can be used for performance modeling and analysis.
Verdejo, and Bholanathsingh Surajbali.
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Prudent capacity planning to meet their clients future computational needs is one of the major issues cloud computing providers face today.
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In this paper we define the interval overlapping relation and develop a parallel hardware unit for its realization.
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September 2012, Acceptance Rate (Full Paper): 19.
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Simple formulas for the arithmetic operations can be applied.
We study a deployment of the SPECjms2007 standard benchmark on a leading commercial middleware platform.
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We tested the functionality, correctness and performance of our implementation in different case studies and compared it with other implementations.
Introduction to queueing petri nets: Modeling formalism, tool support and case studies (tutorial paper).
Performance modelling of concurrency control schemes for relational databases.
Proceedings of the 3rd IEEE International Conference on Cloud and Green Computing (CGC 2013), Karlsruhe, Germany, 2013.
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Aiming at the general power function for inclusion in interval libraries, which is defined for as many pairs of base and exponent as possible, we observe that the definition of a power for each such pair depends on the context.
This raises the challenge of guaranteeing system performance and scalability while at the same time ensuring efficient resource usage.
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Systematic adoption of genetic programming for deriving software performance curves.
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IEEE, New York, USA.
Usually an accumulator is realized as a memory block with operations to add floating point numbers and products.
With the increasing adoption of virtualization and the transition towards Cloud Computing platforms, modern business information systems are becoming increasingly complex and dynamic.
The results demonstrate the effectiveness, practicality and accuracy of the proposed modeling and prediction approach.
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Furthermore we discuss the advantages of this algorithm for a hardware implementation.
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As one application we consider the interval comparisons.
For this purpose we have investigated different dynamic load balancing methods to get an evenly balanced workload during the parallel computation.
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For a further improvement of the run time performance we try to move as many functionality as possible to the compile time using template meta programming techniques.
Aware Resource Reservations in IaaS Environments.
Variants of the general interval power function.
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Our goal is to perform interval operations as fast as their floating point counterparts.
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We show how the expression tree of expression templates can be used to generate problem specific OpenCL kernels.
Reza Sadeghi, and Bhargava Shastry.
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However, given that adaptation processes are usually highly system specific, it is a challenge to abstract from system details enabling the reuse of adaptation strategies.
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Applications in these areas typically have stringent requirements for performance and scalability.
Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and analyzing their performance and scalability.
In this paper we discuss a parallel variant of the interval Newton method for root finding of non linear continuously differentiable functions on the CUDA architecture.
The methodology, which is based on queueing Petri nets, provides a basis for performance analysis and capacity planning.
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The article gives an overview of power function variants and compares three differently extensive versions for use in interval arithmetics.
In such scenarios, complex adaptations to changes in the system environment are still largely performed manually by humans.
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Customers may reserve capacity deviating from their truly predicted demand, in order to exploit the mechanism for their own benefit, thereby causing futile costs for the provider.
We provide a unified treatment to handle the variants and present valuable implementation techniques for the computation of these interval functions along with a mathematic foundation.
Improving Accuracy of Software Performance Models on Multicore Platforms with Shared Caches.
The cache is used to store the carries or borrows, instead of propagating them through the whole accumulator every time.
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