VGRIS
2013pp. 203–214
Citations Over TimeTop 10% of 2013 papers
Abstract
Fueled by the maturity of virtualization technology for Graphics Processing Unit (GPU), there is an increasing number of data centers dedicated to GPU-related computation tasks in cloud gaming. However, GPU resource sharing in these applications is usually poor. This stems from the fact that the typical cloud gaming service providers often allocate one GPU exclusively for one game. To achieve the efficiency of computational resource management, there is a demand for cloud computing to employ the multi-task scheduling technologies to improve the utilization of GPU.
Related Papers
- → Parallel connected-component labeling algorithm for GPGPU applications(2010)14 cited
- Parallel Programming For High-Performance Computing on CUDA(2009)
- CUDA-NP： Realizing Nested Thread-Level Parallelism in GPGPU Applications(2015)
- Introductory on GPGPU Programming Technique(2010)
- → Новітні архітектури відеоадаптерів. Технологія GPGPU. Частина 2(2013)