@conference{10.1145/2925426.2926253,
title = {Tag-Split Cache for Efficient GPGPU Cache Utilization},
author = {Lingda Li and Ari B Hayes and Shuaiwen Leon Song and Eddy Z Zhang},
url = {https://doi.org/10.1145/2925426.2926253},
doi = {10.1145/2925426.2926253},
isbn = {9781450343619},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 2016 International Conference on Supercomputing (ICS 2016)},
publisher = {Association for Computing Machinery},
address = {Istanbul, Turkey},
abstract = {Modern GPUs employ cache to improve memory system efficiency. However, large amount of cache space is underutilized due to irregular memory accesses and poor spatial locality which exhibited commonly in GPU applications. Our experiments show that using smaller cache lines could improve cache space utilization, but it also frequently suffers from significant performance loss by introducing large amount of extra cache requests. In this work, we propose a novel cache design named tag-split cache (TSC) that enables fine-grained cache storage to address the problem of cache space underutilization while keeping memory request number unchanged. TSC divides tag into two parts to reduce storage overhead, and it supports multiple cache line replacement in one cycle. TSC can also automatically adjust cache storage granularity to avoid performance loss for applications with good spatial locality. Our evaluation shows that TSC improves the baseline cache performance by 17.2% on average across a wide range of applications. It also out-performs other previous techniques significantly.},
keywords = {Cache organization, GPGPU, Spatial Locality},
pubstate = {published},
tppubtype = {conference}
}