Managing gpu buffers for caching more apps in mobile systems

Abstract

Modern mobile systems cache apps actively to quickly respond to a user's call to launch apps. Since the amount of usable memory is critical to the number of cacheable apps, it is important to maximize memory utilization. Meanwhile, modern mobile apps make use of graphics processing units (GPUs) to accelerate their graphic operations and to provide better user experience. In resource-constrained mobile systems, GPU cannot afford its private memory but shares the main memory with CPU. It leads to a considerable amount of main memory to be allocated for GPU buffers which are used for processing GPU operations. These GPU buffers are, however, not managed effectively so that inactive GPU buffers occupy a large fraction of the memory and decrease memory utilization. This paper proposes a scheme to manage GPU buffers to increase the memory utilization in mobile systems. Our scheme identifies inactive GPU buffers by exploiting the state of an app from a user's perspective, and reduces their memory footprint by compressing them. Our sophisticated design approach prevents GPU-specific issues from causing an unpleasant overhead. Our evaluation on a running prototype with realistic workloads shows that the proposed scheme can secure up to 215.9 MB of extra memory from 1.5 GB of main memory and increase the average number of cached apps by up to 31.3%.