… In our case we use a set of OpenCL programs that are both executed on the CPU and the
GPU to measure the speedup of the GPU execution for each individual kernel over the CPU. …

… GPUs, allowing multitasking to take place. Virtual GPUs are activated by specifying weights
of GPU … This paper presents Smart Scheduler; an approach of improving throughput together …

… In this paper, we focus on the integrated CPU+GPU processors, where the CPU and GPU
devices share a total power budget and have strong thermal interactions since the two devices …

… , CPU or GPU… scheduler for Kubernetes environment using machine learning based on
runtime prediction of the applications in order to better select the appropriate device, CPU or GPU…

… -GPU (CPU+GPU) and a multiaccelerator (CPU+GPU+MIC) environments, we observe that,
in general, the SSMART scheduler … hand-tuned native versions for GPU and MIC. Moreover, …

… and CPU-GPU utilization. We also deduce job execution energy consumption and the optimal
CPU-GPU utilization. • Thirdly, we provide a systems computing node CPUGPU utilization …

… We propose a scheduler named Troodon that is capable to assign jobs to CPUs and GPUs
in a load balanced manner while taken into consideration the job processing requirement, …

… on any CPU and GPU resources. The rise … smart heterogeneity-aware resource scheduling,
and is able to perform at par with or better compared to the state-of-the-art GPU schedulers …

… In general, the current programming frameworks for CPU-GPU heterogeneous … multicore
CPUs and GPUs. In this survey paper we review the various techniques available for CPU-GPU …

… a CPU with a GPU can convey the ideal estimation of framework cost, execution and power.
It tends to be expressed that GPUs vary from CPUs as GPU … expense effectively than CPUs. …