Matching Items (3)
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- All Subjects: Mobile
- Creators: Wu, Carole-Jean
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 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.
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
Description
The Mobile Waterway Monitor seeks to monitor water in an unexplored way. The module is buoyant and will float with the current as well as harvests solar energy. In short, the Mobile Waterway Monitor excels in size constraints, flexibility, extensibility, and capability. This current following monitor can show both measured trends like pH and interpolated trends like water speed, river contours, and elevation drop. The MWM strikes a balance between accuracy, portability, and being multi-purpose.
ContributorsStribrny, Kody John (Author) / Vrudhula, Sarma (Thesis director) / Wu, Carole-Jean (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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 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