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Анализ производительности Java на устройствах Android с помощью Intel® VTune™ Amplifier 2014 for Systems

Intel® VTune™ Amplifier 2014 for Systems поддерживает анализ функций Java и доступ к ассемблеру с JIT, Java Source и Dex* для функций, обработанных с помощью JIT на рутованных устройствах Android*, на которых запущена виртуальная машина Java/Dalvik* с оснасткой.  Прочтите эту статью позже, чтобы узнать, как запустить будущую версию VTune Amplifier for Systems для включения анализа Java на ART* JVM.

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  • Intel® XDK Install Instructions

    Note that the APIs listed below augment the standard Cordova APIs, both APIs can and should be used in your application. In some cases there is overlap between the Cordova APIs and the intel.xdk APIs; in that case, we recommend you use the Cordova API first and then use the intel.xdk API when the Cordova API either does not provide the desired functionality or provides inadequate functionality.

    Intel® XDK Install Instructions

    Note that the APIs listed below augment the standard Cordova APIs, both APIs can and should be used in your application. In some cases there is overlap between the Cordova APIs and the intel.xdk APIs; in that case, we recommend you use the Cordova API first and then use the intel.xdk API when the Cordova API either does not provide the desired functionality or provides inadequate functionality.
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    Improve Intel MKL Performance for Small Problems: The Use of MKL_DIRECT_CALL

    One of the big new features introduced in the Intel MKL 11.2 is the greatly improved performance for small problem sizes. In 11.2, this improvement focuses on xGEMM functions (matrix multiplication). Out of the box, there is already a version-to-version improvement (from Intel MKL 11.1 to Intel MKL 11.2). But on top of it, Intel MKL introduces a new control that can lead to further significant performance boost for small matrices. Users can enable this control when linking with Intel MKL by specifying "-DMKL_DIRECT_CALL" or "-DMKL_DIRECT_CALL_SEQ".

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  • Is __kmp_suspend_initialize_thread race free?

    Hi,

    I work with just another tool for data race detection. I repeatedly got messages about a data race between the pthread_mutex_init in __kmp_suspend_initialize_thread and the pthread_mutex_lock. After analysis of the situation, I think there is actually a possible race condition.

    The only synchronization for the init_mutex I could find was the

    if(th->th.th_suspend_init_count > __kmp_fork_count){...}

    surrounding it. I think the init_mutex should be guarded like:

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