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ART vs Dalvik* - 介绍全新的安卓* x86运行时

Android* 5.x 一项最显著的变化是迁移至新的应用执行方法,称为 Android 运行时 (ART)。 Android 4.4 (KitKat) 发布后,随即提供了 ART 选项。 KitKat 用户可以选择 使用 ART 或其前任 Dalvik。 现在,ART 是 Android Lollipop 中唯一的运行时环境。

运行相同 Dex 字节代码时,ART 和 Dalvik 能够兼容,因此针对 Dalvik 开发的应用 基于 ART 运行的时候也可有良好表现。 本文将介绍 ART 的不同之处

让我们来看看 ART 的主要特性。

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  • ART vs Dalvik* - Introducing the New Android* x86 Runtime

    One of the most significant Android* 5.x changes is the shift to the relatively new way of executing applications called Android Runtime (ART). The option to use ART has been available since the Android 4.4 (KitKat) release. KitKat users had a choice between ART and its predecessor Dalvik. Now ART is the only runtime environment in Android Lollipop.

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  • 在 x86 上优化 Android 应用的方法和技巧

    英特尔致力于帮助开发人员提供能够在英特尔架构上正常运行(甚至出色运行)的 Android 应用。 虽然英特尔主要致力于社区层面:优化 Dalvik Java、V8 引擎和 Bionic C;丰富代码库;为 IA 提供采用 32 位和 64 位内核的版本,他们同样提供了多种类型的新工具为 Android 开发人员提供帮助。 这些工具主要用于提高性能,使其超过面向 x86 的默认 ARM 转换层:libhoudini 所提供的性能。

    但是首先需要选择合适的工具。 创建 Android 应用有 3 种常见的方法。

    Tips and Tricks to Optimize Android Apps on x86

    Intel has a vested interest in helping developers provide Android applications that run well (or even best) on Intel architecture. While Intel is working at the community level - optimizing Dalvik Java, V8 engine, and Bionic C; contributing to the code base; and providing releases with both 32 bit and 64-bit Kernels for IA; they are also creating new tools to help  Android developers. Many of these focus on improving performance beyond that available with the default ARM translation layer for x86: libhoudini

    Java vs C vs IPP vs TBB: test di performance su dispositivi Intel

    Di recente ci siamo trovati nella situazione di voler ottimizzare una nostra applicazione per la realta’ aumentata (http://picshare.jooink.com) su dispositivi mobile. Picshare e' interamente scritto in javascript ed essendo il nostro target quello di ottimizzarlo per dispositivi mobile la strada più naturale ci è sembrata quella di riscrivere nativamente parte degli algoritmi computazionalmente rilevanti e, con l’occasione, mettere a confronto diverse implementazioni ‘native’ al fine di capire quale strategia fosse preferibile.

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