Yuhao Zhu

WebCore: architectural support for mobileweb browsing

The Web browser is undoubtedly the single most important application in the mobile ecosystem. An average user spends 72 minutes each day using the mobile Web browser. Web browser internal engines (e.g., WebKit) are also growing in importance because they provide a common substrate for developing various mobile Web applications. In a user-driven, interactive, and latency-sensitive environment, the browsers performance is crucial. However, the battery-constrained nature of mobile devices limits the performance that we can deliver for mobile Web browsing. As traditional general-purpose techniques to improve performance and energy efficiency fall short, we must employ domain-specific knowledge while still maintaining general-purpose flexibility. In this paper, we first perform design-space exploration to identify appropriate general-purpose architectures that uniquely fit the characteristics of a popular Web browsing engine. Despite our best effort, we discover sources of energy inefficiency in these customized general-purpose architectures. To mitigate these inefficiencies, we propose, synthesize, and evaluate two new domain-specific specializations, called the Style Resolution Unit and the Browser Engine Cache. Our optimizations boost energy efficiency and at the same time improve mobile Web browsing performance. As emerging mobile workloads increasingly rely more on Web browser technologies, the type of optimizations we propose will become important in the future and are likely to have lasting widespread impact.

Mobile CPU's rise to power: Quantifying the impact of generational mobile CPU design trends on performance, energy, and user satisfaction

In this paper, we assess the past, present, and future of mobile CPU design. We study how mobile CPU designs trends have impacted the end-user, hardware design, and the holistic mobile device. We analyze the evolution often cutting-edge mobile CPU designs released over the past seven years. Specifically, we report measured performance, power, energy and user satisfaction trends across mobile CPU generations. A key contribution of our work is that we contextualize the mobile CPUs evolution in terms of user satisfaction, which has largely been absent from prior mobile hardware studies. To bridge the gap between mobile CPU design and user satisfaction, we construct and conduct a novel crowdsourcing study that spans over 25,000 survey participants using the Amazon Mechanical Turk service. Our methodology allows us to identify what mobile CPU design techniques provide the most benefit to the end-users quality of user experience. Our results quantitatively demonstrate that CPUs play a crucial role in modern mobile system-on-chips (SoCs). Over the last seven years, both single-and multicore performance improvements have contributed to end-user satisfaction by reducing user-critical application response latencies. Mobile CPUs aggressively adopted many power-hungry desktop-oriented design techniques to reach these performance levels. Unlike other smartphone components (e.g. display and radio) whose peak power consumption has decreased over time, the mobile CPUs peak power consumption has steadily increased. As the limits of technology scaling restrict the ability of desktop-like scaling to continue for mobile CPUs, specialized accelerators appear to be a promising alternative that can help sustain the power, performance, and energy improvements that mobile computing necessitates. Such a paradigm shift will redefine the role of the CPU within future SoCs, which merit several design considerations based on our findings.

Mosaic: cross-platform user-interaction record and replay for the fragmented android ecosystem

In contrast to traditional computing systems, such as desktops and servers, that are programmed to perform “compute-bound” and “run-to-completion” tasks, mobile applications are designed for user interactivity. Factoring user interactivity into computer system design and evaluation is important, yet possesses many challenges. In particular, systematically studying interactive mobile applications across the diverse set of mobile devices available today is difficult due to the mobile device fragmentation problem. At the time of writing, there are 18,796 distinct Android mobile devices on the market and will only continue to increase in the future. Differences in screen sizes, resolutions and operating systems impose different interactivity requirements, making it difficult to uniformly study these systems. We present Mosaic, a cross-platform, timing-accurate record and replay tool for Android-based mobile devices. Mosaic overcomes device fragmentation through a novel virtual screen abstraction. User interactions are translated from a physical device into a platform-agnostic intermediate representation before translation to a target system. The intermediate representation is human-readable, which allows Mosaic users to modify previously recorded traces or even synthesize their own user interactive sessions from scratch. We demonstrate that Mosaic allows user interaction traces to be recorded on emulators, smartphones, tablets, and development boards and replayed on other devices. Using Mosaic we were able to replay 45 different Google Play applications across multiple devices, and also show that we can perform cross-platform performance comparisons between two different processors under identical user interactions.

Microarchitectural implications of event-driven server-side web applications

Enterprise Web applications are moving towards server-side scripting using managed languages. Within this shifting context, event-driven programming is emerging as a crucial programming model to achieve scalability. In this paper, we study the microarchitectural implications of server-side scripting, JavaScript in particular, from a unique event-driven programming model perspective. Using the Node.js framework, we come to several critical microarchitectural conclusions. First, unlike traditional server-workloads such as CloudSuite and BigDataBench that are based on the conventional thread-based execution model, event-driven applications are heavily single-threaded, and as such they require significant single-thread performance. Second, the single-thread performance is severely limited by the front-end inefficiencies of todays server processor microarchitecture, ultimately leading to overall execution inefficiencies. The front-end inefficiencies stem from the unique combination of limited intra-event code reuse and large inter-event reuse distance. Third, through a deep understanding of event-specific characteristics, architects can mitigate the front-end inefficiencies of the managed-language-based event-driven execution via a combination of instruction cache insertion policy and prefetcher.

GreenWeb: language extensions for energy-efficient mobile web computing

Web computing is gradually shifting toward mobile devices, in which the energy budget is severely constrained. As a result, Web developers must be conscious of energy efficiency. However, current Web languages provide developers little control over energy consumption. In this paper, we take a first step toward language-level research to enable energy-efficient Web computing. Our key motivation is that mobile systems can wisely budget energy usage if informed with user quality-of-service (QoS) constraints. To do this, programmers need new abstractions. We propose two language abstractions, QoS type and QoS target, to capture two fundamental aspects of user QoS experience. We then present GreenWeb, a set of language extensions that empower developers to easily express the QoS abstractions as program annotations. As a proof of concept, we develop a GreenWeb runtime, which intelligently determines how to deliver specified user QoS expectation while minimizing energy consumption. Overall, GreenWeb shows significant energy savings (29.2% ∼ 66.0%) over Android’s default Interactive governor with few QoS violations. Our work demonstrates a promising first step toward language innovations for energy-efficient Web computing.

Estimation of instantaneous frequency fluctuation in a fast DVFS environment using an empirical BTI stress-relaxation model

This work proposes an empirical Bias Temperature Instability (BTI) stress-relaxation model based on the superposition property. The model was used to study the instantaneous frequency fluctuation in a fast Dynamic Voltage and Frequency Scaling (DVFS) environment. VDD and operating frequency information for this study were collected from an ARM Cortex A15 processor based development board running an Android operating system. Simulation results show that the frequency peaks and dips are functions of mainly two parameters: (1) the amount of stress or recovery experienced by the circuit prior to the VDD switching and (2) the frequency sensitivity to device aging after the VDD switching.

Optimizing General-Purpose CPUs for Energy-Efficient Mobile Web Computing

Mobile applications are increasingly being built using web technologies as a common substrate to achieve portability and to improve developer productivity. Unfortunately, web applications often incur large performance overhead, directly affecting the user quality-of-service (QoS) experience. Traditional techniques in improving mobile processor performance have mostly been adopting desktop-like design techniques such as increasing single-core microarchitecture complexity and aggressively integrating more cores. However, such a desktop-oriented strategy is likely coming to an end due to the stringent energy and thermal constraints that mobile devices impose. Therefore, we must pivot away from traditional mobile processor design techniques in order to provide sustainable performance improvement while maintaining energy efficiency. In this article, we propose to combine hardware customization and specialization techniques to improve the performance and energy efficiency of mobile web applications. We first perform design-space exploration (DSE) and identify opportunities in customizing existing general-purpose mobile processors, that is, tuning microarchitecture parameters. The thorough DSE also lets us discover sources of energy inefficiency in customized general-purpose architectures. To mitigate these inefficiencies, we propose, synthesize, and evaluate two new domain-specific specializations, called the Style Resolution Unit and the Browser Engine Cache. Our optimizations boost performance and energy efficiency at the same time while maintaining general-purpose programmability. As emerging mobile workloads increasingly rely more on web technologies, the type of optimizations we propose will become important in the future and are likely to have a long-lasting and widespread impact.

Cognitive Computing Safety: The New Horizon for Reliability / The Design and Evolution of Deep Learning Workloads

This column includes two invited position papers about the challenges and opportunities in cognitive architectures.

Research for practice: web security and mobile web computing

Our third installment of Research for Practice brings readings spanning programming languages, compilers, privacy, and the mobile web.