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Description
A benchmark suite that is representative of the programs a processor typically executes is necessary to understand a processor's performance or energy consumption characteristics. The first contribution of this work addresses this need for mobile platforms with MobileBench, a selection of representative smartphone applications. In smartphones, like any other

A benchmark suite that is representative of the programs a processor typically executes is necessary to understand a processor's performance or energy consumption characteristics. The first contribution of this work addresses this need for mobile platforms with MobileBench, a selection of representative smartphone applications. In smartphones, like any other portable computing systems, energy is a limited resource. Based on the energy characterization of a commercial widely-used smartphone, application cores are found to consume a significant part of the total energy consumption of the device. With this insight, the subsequent part of this thesis focuses on the portion of energy that is spent to move data from the memory system to the application core's internal registers. The primary motivation for this work comes from the relatively higher power consumption associated with a data movement instruction compared to that of an arithmetic instruction. The data movement energy cost is worsened esp. in a System on Chip (SoC) because the amount of data received and exchanged in a SoC based smartphone increases at an explosive rate. A detailed investigation is performed to quantify the impact of data movement

on the overall energy consumption of a smartphone device. To aid this study, microbenchmarks that generate desired data movement patterns between different levels of the memory hierarchy are designed. Energy costs of data movement are then computed by measuring the instantaneous power consumption of the device when the micro benchmarks are executed. This work makes an extensive use of hardware performance counters to validate the memory access behavior of microbenchmarks and to characterize the energy consumed in moving data. Finally, the calculated energy costs of data movement are used to characterize the portion of energy that MobileBench applications spend in moving data. The results of this study show that a significant 35% of the total device energy is spent in data movement alone. Energy is an increasingly important criteria in the context of designing architectures for future smartphones and this thesis offers insights into data movement energy consumption.
ContributorsPandiyan, Dhinakaran (Author) / Wu, Carole-Jean (Thesis advisor) / Shrivastava, Aviral (Committee member) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Virtual machines and containers have steadily improved their performance over time as a result of innovations in their architecture and software ecosystems. Network functions and workloads are increasingly migrating to virtual environments, supported by developments in software defined networking (SDN) and network function virtualization (NFV). Previous performance analyses

Virtual machines and containers have steadily improved their performance over time as a result of innovations in their architecture and software ecosystems. Network functions and workloads are increasingly migrating to virtual environments, supported by developments in software defined networking (SDN) and network function virtualization (NFV). Previous performance analyses of virtual systems in this context often ignore significant performance gains that can be acheived with practical modifications to hypervisor and host systems. In this thesis, the network performance of containers and virtual machines are measured with standard network performance tools. The performance of these systems utilizing a standard 3.18.20 Linux kernel is compared to that of a realtime-tuned variant of the same kernel. This thesis motivates improving determinism in virtual systems with modifications to host and guest kernels and thoughtful process isolation. With the system modifications described, the median TCP bandwidth of KVM virtual machines over bridged network interfaces, is increased by 10.8% with a corresponding reduction in standard deviation of 87.6%. Docker containers see a 8.8% improvement in median bandwidth and 4.4% reduction in standard deviation of TCP measurements using similar bridged networking. System tuning also reduces the standard deviation of TCP request/response latency (TCP RR) over bridged interfaces by 86.8% for virtual machines and 97.9% for containers. Hardware devices assigned to virtual systems also see reductions in variance, although not as noteworthy.
ContributorsWelch, James Matthew (Author) / Syrotiuk, Violet R. (Thesis advisor) / Wu, Carole-Jean (Committee member) / Speyer, Gil (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The availability of a wide range of general purpose as well as accelerator cores on

modern smartphones means that a significant number of applications can be executed

on a smartphone simultaneously, resulting in an ever increasing demand on the memory

subsystem. While the increased computation capability is intended for improving

user experience, memory requests

The availability of a wide range of general purpose as well as accelerator cores on

modern smartphones means that a significant number of applications can be executed

on a smartphone simultaneously, resulting in an ever increasing demand on the memory

subsystem. While the increased computation capability is intended for improving

user experience, memory requests from each concurrent application exhibit unique

memory access patterns as well as specific timing constraints. If not considered, this

could lead to significant memory contention and result in lowered user experience.

This work first analyzes the impact of memory degradation caused by the interference

at the memory system for a broad range of commonly-used smartphone applications.

The real system characterization results show that smartphone applications,

such as web browsing and media playback, suffer significant performance degradation.

This is caused by shared resource contention at the application processor’s last-level

cache, the communication fabric, and the main memory.

Based on the detailed characterization results, rest of this thesis focuses on the

design of an effective memory interference mitigation technique. Since web browsing,

being one of the most commonly-used smartphone applications and represents many

html-based smartphone applications, my thesis focuses on meeting the performance

requirement of a web browser on a smartphone in the presence of background processes

and co-scheduled applications. My thesis proposes a light-weight user space frequency

governor to mitigate the degradation caused by interfering applications, by predicting

the performance and power consumption of web browsing. The governor selects an

optimal energy-efficient frequency setting periodically by using the statically-trained

performance and power models with dynamically-varying architecture and system

conditions, such as the memory access intensity of background processes and/or coscheduled applications, and temperature of cores. The governor has been extensively evaluated on a Nexus 5 smartphone over a diverse range of mobile workloads. By

operating at the most energy-efficient frequency setting in the presence of interference,

energy efficiency is improved by as much as 35% and with an average of 18% compared

to the existing interactive governor, while maintaining the satisfactory performance

of web page loading under 3 seconds.
ContributorsShingari, Davesh (Author) / Wu, Carole-Jean (Thesis advisor) / Vrudhula, Sarma (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2016