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This new paradigm is gaining an expanding interest, since it provides cost efficient architectures that support the transmission, storage, and intensive computing of data.
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Small businesses are already under pressure to embrace new technology trends such as bring your own device (BYOD) and cloud computing storage of data and applications in order to be more competitive.
Both simulators have a built-in functionality of computing sensitivity of data to reservoir parameters using the Adjoint-State approach.
Hadoop provides the MapReduce programming model, by which parallel computing of large data sets can be implemented in the cloud computing environment.
Amazon Web Services has come to dominate the cloud computing business, at least for the so-called "public" clouds where large and small business store and compute lots of data.
Use (35) to compute reliability of data carriers, ℜ ( k ) k = 1 P, with 1≤P≤N and rearrange them in decreasing order of their reliability.
In cloud computing, huge resources of data storage, computation and communications exist in remote structures with thousands of computers.
Factored HMMs offer computational benefits when computing the likelihood of data.
In addition, as predicted from complexity analysis, the runtime of computing probabilities at all loci is twice that of computing the likelihood of data.
Indeed, the cost of storing and computing large quantities of data has dropped dramatically over the past decade.
Google has used a similar approach — immense computing power, heaps of data and statistics — to tackle other complex problems.
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