Inefficiencies in the Cache Hierarchy: A Sensitivity Study of Cacheline Size with Mobile Workloads

With the rising number of cores in mobile devices, the cache hierarchy in mobile application processors gets deeper, and the cache size gets bigger. However, the cacheline size remained relatively constant over the last decade in mobile application processors. In this work, we investigate whether the cacheline size in mobile application processors is due for a refresh, by looking at inefficiencies in the cache hierarchy which tend to be exacerbated when increasing the cacheline size: false sharing and cacheline utilization. Firstly, we look at false sharing, which is more likely to arise at larger cacheline sizes and can severely impact performance. False sharing occurs when non-shared data structures, mapped onto the same cacheline, are being accessed by threads running on different cores, causing avoidable invalidations and subsequent misses. False sharing has been found in various places such as scientific workloads and real applications. We find that whilst increasing the cacheline size does increase false sharing, it still is negligible when compared to known cases of false sharing in scientific workloads, due to the limited level of thread-level parallelism in mobile workloads. Secondly, we look at cacheline utilization which measures the number of bytes in a cacheline actually used by the processor. This effect has been investigated under various names for a multitude of server and desktop applications. As a low cacheline utilization implies that very little of the fetched cachelines was used by the processor, this causes waste in bandwidth and energy in moving data across the memory hierarchy. The energy cost associated with data movements is much higher compared to logic operations, increasing the need for cache efficiency, especially in the case of an energy-constrained platform like a mobile device. We find that the cacheline utilization of mobile workloads is low in general, decreasing when increasing the cacheline size. When increasing the cacheline size from 64 bytes to 128 bytes, the number of misses will be reduced by 10%-30%, depending on the workload. However, because of the low cacheline utilization, this more than doubles the amount of unused traffic to the L1 caches. Using the cacheline utilization as a metric in this way, illustrates an important point. If a change in cacheline size would only be assessed on its local effects, we find that this change in cacheline size will only have advantages as the miss rate decreases. However, at system level, this change will increase the stress on the bus and increase the amount of wasted energy due to unused traffic. Using cacheline utilization as a metric underscores the need for system-level research when changing characteristics of the cache hierarchy

A survey of emerging architectural techniques for improving cache energy consumption

The search goes on for another ground breaking phenomenon to reduce the ever-increasing disparity between the CPU performance and storage. There are encouraging breakthroughs in enhancing CPU performance through fabrication technologies and changes in chip designs but not as much luck has been struck with regards to the computer storage resulting in material negative system performance. A lot of research effort has been put on finding techniques that can improve the energy efficiency of cache architectures. This work is a survey of energy saving techniques which are grouped on whether they save the dynamic energy, leakage energy or both. Needless to mention, the aim of this work is to compile a quick reference guide of energy saving techniques from 2013 to 2016 for engineers, researchers and students