Since each compute node in our test cluster has a GPU attached to it, every node accelerates the Compute-Interactions phase of the algorithm on the dedicated GPU device, while performing the rest of the computations on the CPU.
Therefore, in terms of interaction between the algorithm and the subject via insulin dosing, the six subjects participating in two experiments each were indistinguishable from 12 subjects each participating in a single experiment.
In addition, results indicate that the six first interactions of the ZAP algorithm achieve 99% of the performance that could be achieved if an infinite number of interactions, regardless of the network size or network density, were carried out.
Aiming to reduce the dynamic interaction time of the sync algorithm, the concept of ε-neighborhood closures is proposed in the SHC algorithm.
The SHC algorithm proposes the concept of neighborhood closures reducing dynamic interaction time of the sync algorithm.
Moreover, we have observed limitations of the GraphAlignment algorithm in comparison of yeast and human protein-protein interaction networks, where the performance of the algorithm is decreased, most probably because the Bayesian scheme cannot deal with biased data or with the heterogenous rate of edge dynamics.
In this case, the train score is so low, that the addition of the physical interaction score prevents the algorithm from adding regulators, even if they are correct.
Several novel multiscale physical interactions are identified, highlighting the utility of the algorithm and the potential importance of spatiotemporal modulation of the convective flow on the mean dynamics.
If the interacting cells are well separated, the interaction is approximated using the M2L kernel (equation (3b)), which computes and accumulates the local field tensors F n m ( s B ) for the expansion of gravity within the sink cell B and due to all sources within the source cell A (in a mutual version of the algorithm, the interactions A → B and B → A are considered simultaneously).
In particular, we aim to explore whether it is possible to cover more general interactions without increasing the computational complexity of the algorithm.
