RDDs addresses the problem of data reuse of intermediate results among multiple computations, which cannot be handled efficiently by current proposed cluster computing frameworks such as MapReduce and Dryad [25].
The FEM with heterogeneity material model allows every computation produces a different result, which thus can be taken as a virtual test for NFRC structures, and the statistical result can be obtained according to multiple computations.
Although bias-corrected bootstrap seems to be a useful method to be used in youth treatment outcome studies, product of coefficient test may be more suitable for very small samples and more feasible in terms of programs and steps that are needed to conduct the analyses (i.e., regression in SPSS vs. multiple computations in AMOS or EQS) [MacKinnon et al. 2004].
Then Λ2 is called s-compatible to Λ1 if there exist some rule Λ3 such that L v 2 ′ = L v 2 + L v 3 and L v = L v 1 + L v 2 ′. Figure 3B depicts two such ways that realize the same optimal solution L v. Sparsification prunes any such multiple computations of the same optimal value.
At present, a promising solution to address this challenge is cloud computing [ 3- 5], which exploits the full potential of multiple computers and delivers computation and storage as dynamically allocated virtual resources via the Internet [ 6].
The upgraded edition of CU-ENUF runs concurrently in a hybrid parallel way that enables the computation parallelizing on multiple computer nodes firstly, then further on the installed GPU in each computer.
We write scripts to distribute the computation among multiple cores/CPUs and run multiple computing analyses simultaneously.
The runtime cost of adaptive computations leads to an important resource management issue, i.e., how to allocate the current available resources among adaptive computations and business functions, as well as among multiple adaptive computations.
