1. A method, comprising: configuring a shared library, stored in a memory, to be loaded into applications to intercept graphics processing unit (GPU) computation requests for different types of workload kernals corresponding to the applications; generating a power prediction and a performance prediction for at least one candidate kernel combination for execution on a GPU responsive to the GPU computations requests, the at least one candidate kernel combination pertaining to at least two of the workload kernals; and rendering a decision of whether to execute the at least one candidate kernel combination or to execute the at least two of the workload kernals pertaining thereto separately, based on the power prediction and the performance prediction.