An Evaluation of Intel Cache Allocation Technology for Data- Intensive Applications

Detta är en Master-uppsats från KTH/Skolan för elektroteknik och datavetenskap (EECS)

Sammanfattning: On certain CPUs part of the Intel Xeon Scalable CPU family, the level three (L3) cache is shared among the CPU cores residing on the same CPU socket. This has benefits in that a larger and more scalable cache space is available to the CPU cores. However, when the L3 cache is shared between CPU cores and thereby by the applications running there, the applications can affect the performance of each other if some of them have high L3 cache usage. This can be particularly problematic if an application is over-utilizing the L3 cache and effectively evicting the data of other applications, which are more prioritized, from the L3 cache. Such applications are called L3 cache noisy neighbors. The experiments in this thesis study the effect L3 cache noisy neighbors have on other, more prioritized, applications and if Intel Cache Allocation Technology (CAT) can be used to limit the performance impact the noisy neighbors have. Intel CAT provides functionality to control the amount of L3 cache allocated to a CPU core and by allocating less L3 cache to a noisy neighbor it no longer shares as much L3 cache with the prioritized applications and thus the prioritized applications can again utilize more of the L3 cache and regain their performance. The research question of this thesis is to investigate in what cases Intel CAT can provide advantages and where it is a disadvantage to use it by studying its use for three commonly used applications; bzip2, Redis, and Graph500. All the three applications were significantly impacted when running simultaneously with a noisy neighbor and for the Redis application there was a decrease of 49.2% in the number of ’GET’ requests per second that the Redis server could handle and an 18.2% decrease for ’SET’ requests. For the bzip2 and Graph500 applications, there was a 14.7% and 28.1% increase in execution time respectively. Intel CAT was successfully used to limit the impact of the noisy neighbor on the three applications. For the Redis application, the number of requests per second increased by 8.6% for the ’GET’ operation and by 4.2% for the ’SET’ operation. For the bzip2 and Graph500 applications, there was a 5.8% and 12.0% decrease in execution time respectively. Moreover, the thesis studies the scenario when only prioritized applications are running and if their performance can be increased by isolating the L3 cache for each one of them so that they cannot cause L3 cache evictions for each other. The use case of Intel CAT in such a scenario is not as clear as when mitigating the impact of a noisy neighbor but some performance benefits can be observed when running multiple Redis instances on the same machine and isolating some of the L3 cache available to them. 

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