The purpose of this exercise is to understand how the host-device lambda functions work, and how to create a general GPU kernel. Furthermore, differentiating between host and device code paths using __HIP_DEVICE_COMPILE__ macro is demonstrated.
The task is to define two host-device lambda functions that can be passed for the host or the device kernel. Both lambda functions require a single integer argument, and the intended location of these definitions are indicated by #error. The first lambda function does not need to capture anything, but must call the predefined function helloFromThread(const int i). The second lambda function must capture the value of pi, and then must multiply the thread index by the pi, and print this value from each thread.
IMPORTANT NOTE! When using the host-device lambda function with NVIDIA architectures, the following compiler argument must be added for hipcc: --extended-lambda