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Using Multivariate Statistics

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

[서평]「The Unified Modeling Language User Guide」

Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences best current practice of SRE software reliability measurement experience measurement-based analysis of software reliability software fault and failure classification techniques trend analysis in validation and maintenance software reliability and field data analysis software reliability process assessment emerging techniques software reliability prediction metrics software reliability and testing fault-tolerant SRE software reliability using fault trees software reliability process simulation neural networks and software reliability. Appendices: software reliability tools software failure data set repository.

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Handbook of software reliability engineering

コンピュータ・サイエンス : ACM computing surveys

The present disclosure includes, in a heterogeneous system, receiving a desired speedup of an application as input and performing a static analysis and a dynamic analysis of the application. The dynamic analysis of the application comprises, identifying a set of parameters including, an end-to-end execution time of the application, an execution time of data parallel loops in the application, an execution time of non-data parallel loops in the application, and an amount of physical memory used by each data structure in each data parallel loop. Dynamic analysis also includes calculating and providing the feasibility of achieving the desired speedup of the application based on the identified set of parameters, and satisfaction of each of, an initialization invariant, a data-parallel invariant and a data transfer invariant.

Method and system for analyzing an extent of speedup achievable for an application in a heterogeneous system

Presents an object oriented design environment for modeling as well as synthesis of circuits. The modeling of circuits as classes and storage of presynthesized modules has been discussed. A design approach is presented which synthesizes both the datapath and control path of a circuit from its behavioral specification provided in object oriented style. The synthesis approach can synthesize circuits which reuse the presynthesized modules from the design library. >

An object oriented environment for modeling and synthesis of hardware circuits

Map-Reduce is a popular data-parallel programming model for varied analysis of huge volumes of data. While a multicore and many CPU HPC infrastructure can be used to improve parallelism of map-reduce tasks, IO-bandwidth limitations may make them ineffective. IO-intensive activities are essential in any MapReduce cluster. In HPC nodes, IO-intensive jobs get queued at the IO-resources while the CPU remain underutilized, resulting in a poor performance, high power consumption and thus, energy inefficiency. In this paper, we investigate which power management setting can be used to improve the energy efficiency of IO-intensive MapReduce jobs by performing a thorough empirical study. Our analysis indicates that a constant CPU frequency can reduce the energy consumption of an IO-intensive job, while improving its performance. Consequently, we build a set of regression models to predict the energy consumption of IO-intensive jobs at a CPU frequency for a given input data volume. We obtained same set of models, with different coefficients, for two different types of IO-intensive jobs, which substantiates the suitability of identified models. These models predict respective outcomes with 80% accuracy for 80% of the new test cases.

Improving Energy Efficiency of IO-Intensive MapReduce Jobs

As large scale software development has become more collaborative, and software teams more globally distributed, several studies have explored how developer interaction influences software development outcomes. The emphasis so far has been largely on outcomes like defect count, the time to close modification requests etc. In the paper, we examine data from the Chromium project to understand how different aspects of developer discussion relate to the closure time of reviews. On the basis of analyzing reviews discussed by 2000+ developers, our results indicate that quicker closure of reviews owned by a developer relates to higher reception of information and insights from peers. However, we also find evidence that higher engagement in collaboration by a developer is associated with slower closure of the reviews she owns. Within the scope of our study, these results lead us to conclude that peer review of code may have a distinct dynamic that is facilitated by developers working in relative isolation.

/pdf/the-importance-of-being-isolated-an-empirical-study-on-475c1fcq1j.pdf

The Importance of Being Isolated: An Empirical Study on Chromium Reviews

The efficient use of energy is essential to address concerns of cost and sustainability. Many data centers contain MapReduce clusters to process Big Data applications. A large number of machines and fault tolerance capabilities make MapReduce clusters energy inefficient. In this paper, we present a Configurator based on performance and energy models to improve the energy efficiency of MapReduce systems. Our solution is novel as it takes into account the dependence of the performance and energy consumption of a cluster on MapReduce parameters. While this dependence is known, we are the first to model it and design a Configurator to optimize these parameter settings for maximizing the energy efficiency of MapReduce systems. Our empirical evaluations show that the Configurator can result in up to 50% improvement in the energy efficiency of typical MapReduce applications in two architecturally different clusters.

Santonu Sarkar

Papers

Method and system for analyzing an extent of speedup achievable for an application in a heterogeneous system

An object oriented environment for modeling and synthesis of hardware circuits

Improving Energy Efficiency of IO-Intensive MapReduce Jobs

The Importance of Being Isolated: An Empirical Study on Chromium Reviews

Optimizing MapReduce for energy efficiency