The portability offered by our methodology is validated by modelling a Reinforcement Learning (RL) based RTM for two embedded applications and generating implementations for three different platforms (ARM Cortex-A8, A7 and A15) that all achieve energy savings on the respective platforms.
We also present a detailed example of the comparison of the performance of an automatically generated design against a manually generated implementation of the same computation.
These techniques can be used to generate implementation code for several UI platforms including desktop applications, dynamic websites and mobile applications.
Performance benchmarking results on the RVC-based AES and SHA-2 implementations in both C and Java revealed that the automatically generated implementations can achieve a comparable performance to some manually written reference implementations.
These techniques generate different implementation variants at installation time and select one of these implementation variants either at installation time or at runtime, before the computation starts.
Liu and Ning generated an implementation library and an executable package for ECC.
Table 1 shows the optimal cropping pattern generated from implementation of LP and the profit to each group of farmers.
With the support of the proposed CFD model and wind tunnel experiments, a database of aerodynamic coefficients at low Re will be generated for implementation into the BEM model.
Motif-based alignments of kinase sequences to the catalytic core were first generated by implementation of the Gibbs motif sampling method [125], [126].
