Synchronization

The programmer has specified which data is used by each of the functions. Therefore, regardless of what happened prior to executing this function, this data should be up-to-date on the active device. The class-template Sync was designed to serve exactly this purpose. Let's ignore the Dummy parameter, as it was only necessary to specialize Sync within the scope of Hybrid_ (one of the template peculiarities in C++). Sync expects two template parameters which should correspond to the parents of Hybrid_ (DefaultCPU and DefaultGPU by default). The first argument corresponds to the destination device, i.e. the device executing the current routine, whereas the second argument is the device that currently has the data. By default, noting happens when a Sync object is being instantiated. It is however specialized for two other cases: CPU $\to$ GPU, and GPU $\to$ CPU.

The implementation of Sync won't be listed here, but all it does is call cudaMemcpy, where the direction (e.g. cudaMemcpyHostToDevice) depends on the specialization. An example of the implementation of one of the routines however, is listed below:

Because the data-dependencies of multiplyM1() have been specified as input, they are assumed to reside on the CPU. Therefore, the Sync instantiation uses CPUType as the source and MultiplyM1Device as its destination for both vec1 and vec2. Here, MultiplyM1Device is one of the typedef's from Hybrid_, using the Get facility from the DevicePolicies parameter.