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android - 在 Nexus 4 上进行计算量大的数组处理时，会出现周期性的性能峰值是什么原因造成的？

转载 作者：太空宇宙 更新时间：2023-11-03 11:17:32 25 4
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我是线程的新手(不要因为我下面的实现而杀了我:)，我需要在一个单独的线程上对像素进行多次模糊处理(见下文)。它不是方框模糊的最有效实现(来自 Gaussian Filter without using ConvolveOp)，但性能峰值不会出现在 Nexus 7 平板电脑上，但会出现在 Nexus 4 手机上。

我已经发布了我的测试示例(在 Android 4.2 上运行 - 见下文)。

我不认为这是由 GC 抖动内存引起的(它与峰值不一致)。

我认为这可能与缓存局部性或硬件内存抖动有关 - 但我不确定。

什么会导致尖峰？有时它们会突然发作 - 例如峰值 50%。有时它们起病缓慢 - 例如尖峰单调增加/减少，尖峰如下 -> 5%, 10%, 20%, 10%, 5%.

在进行繁重的数组处理时如何阻止它们发生？

这不会发生在我也测试过的 Nexus 7 平板电脑上(见下面的结果)

附带问题:正确休眠和重新启动我的线程的最佳方法是什么(线程新手)？

主 Activity .java

package com.example.test;

import android.os.Bundle;
import android.app.Activity;

public class MainActivity extends Activity {

    private MainThread thread;

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);

        thread = new MainThread();

        thread.setRunning(true);
        thread.start();

        setContentView(R.layout.activity_main);
    }

    @Override
    protected void onResume() {

        super.onResume();
        thread.setRunning(true);

    }

    @Override
    protected void onPause() {

        super.onPause();
        thread.setRunning(false);

    }

}

主线程.java

package com.example.test;

import android.util.Log;

public class MainThread extends Thread {

    int[] pixels;
    int kernel_rows = 2;
    int kernel_cols = 2;
    int width = 512;
    int height = 512;

    @Override
    public void run() {

        while (running) {

            long start = System.currentTimeMillis();

            for (int row = kernel_rows / 2; row < height - kernel_rows / 2; row++) {
                for (int col = kernel_cols / 2; col < width - kernel_cols / 2; col++) {

                    float pixel = 0;

                    // iterate over each pixel in the kernel
                    for (int row_offset = 0; row_offset < kernel_rows; row_offset++) {
                        for (int col_offset = 0; col_offset < kernel_cols; col_offset++) {

                            // subtract by half the kernel size to center the
                            // kernel
                            // on the pixel in question
                            final int row_index = row + row_offset
                                    - kernel_rows / 2;
                            final int col_index = col + col_offset
                                    - kernel_cols / 2;

                            pixel += pixels[row_index * width + col_index] * 1.0f / 4.0f;

                        }
                    }

                    pixels[row * width + col] = (int) pixel;

                }

            }

            long stop = System.currentTimeMillis();

            long delta = stop - start;

            Log.d("DELTA", Long.toString(delta));

        }

    }

    private boolean running;

    public void setRunning(boolean running) {

        this.pixels = new int[512 * 512];
        this.running = running;

    }

}

日志

Nexus 4 手机(毫秒):

01-13 10:56:05.663: D/DELTA(13507): 76
01-13 10:56:05.773: D/DELTA(13507): 107
01-13 10:56:05.843: D/DELTA(13507): 77
01-13 10:56:05.923: D/DELTA(13507): 75
01-13 10:56:06.053: D/DELTA(13507): 127
01-13 10:56:06.133: D/DELTA(13507): 78
01-13 10:56:06.213: D/DELTA(13507): 81
01-13 10:56:06.293: D/DELTA(13507): 80
01-13 10:56:06.353: D/DELTA(13507): 77
01-13 10:56:06.433: D/DELTA(13507): 79
01-13 10:56:06.513: D/DELTA(13507): 79
01-13 10:56:06.624: D/DELTA(13507): 106
01-13 10:56:06.694: D/DELTA(13507): 76

Nexus 7 平板电脑(毫秒):

01-13 11:01:03.283: D/DELTA(3909): 84
01-13 11:01:03.373: D/DELTA(3909): 85
01-13 11:01:03.453: D/DELTA(3909): 85
01-13 11:01:03.543: D/DELTA(3909): 84
01-13 11:01:03.623: D/DELTA(3909): 85
01-13 11:01:03.703: D/DELTA(3909): 84
01-13 11:01:03.793: D/DELTA(3909): 85
01-13 11:01:03.873: D/DELTA(3909): 84
01-13 11:01:03.963: D/DELTA(3909): 85
01-13 11:01:04.043: D/DELTA(3909): 84

最佳答案

我想我可能已经在某种程度上减轻了 Nexus 4 上的这种影响。计算一致性仍然存在一些可变性，但它是可以忍受的 - 我认为 - 看不到太多巨大的尖峰 - 在线程启动/关闭之外。我已经使用 Android NDK 和 c p_threads 完成了此操作，以生成一个 native 线程，该线程主要由 Java(或者我被告知)单独保留，直到更改或关闭前台应用程序。

代码如下:

主 Activity .java

package com.example.test;

import android.os.Bundle;
import android.app.Activity;

public class MainActivity extends Activity {

    static {

        System.loadLibrary("native");

    }

    private native void init();

    @Override
    protected void onCreate(Bundle savedInstanceState) {

        super.onCreate(savedInstanceState);

        // Initializes and spawns native thread
        init();

        setContentView(R.layout.activity_main);

    }

}

原生.c

(应该放在Android项目根目录下的jni文件夹中)

#include <time.h>
#include <pthread.h>
#include <jni.h>
#include <android/log.h>

#define APPNAME "DELTA"

int* pixels;
int kernel_rows = 2;
int kernel_cols = 2;
int width = 60;
int height = 39;

int running = 1;

// from android samples
/* return current time in milliseconds */
static double now_ms(void) {

    struct timespec res;
    clock_gettime(CLOCK_REALTIME, &res);
    return 1000.0 * res.tv_sec + (double) res.tv_nsec / 1e6;

}

// initialize thread/begin it
jint Java_com_example_testa_MainActivity_init(JNIEnv* env, jobject javaThis) {

    int i1 = 1;

    pthread_t thread;
    void *run();

    pthread_create(&thread, NULL, run, &i1);
    pthread_join(thread, NULL);

    return 0;

}

// thread function
void *run(int *x) {

    // init pixels within thread
    pixels = (int*) malloc(sizeof(int) * width * height);

    // loop until stopped - java won't interfere
    // unless closed/switch application (or so I'm told)
    while (running) {

        double start = now_ms();

        int row, col, row_offset, col_offset;

        for (row = kernel_rows / 2; row < height - kernel_rows / 2; row++) {

            for (col = kernel_cols / 2; col < width - kernel_cols / 2; col++) {

                float pixel = 0;

                // iterate over each pixel in the kernel
                for (row_offset = 0; row_offset < kernel_rows; row_offset++) {
                    for (col_offset = 0; col_offset < kernel_cols;
                            col_offset++) {

                        // subtract by half the kernel size to center the
                        // kernel
                        // on the pixel in question

                        int row_index = row + row_offset - kernel_rows / 2;
                        int col_index = col + col_offset - kernel_cols / 2;

                        pixel += pixels[row_index * width + col_index] * 1.0f
                                / 4.0f;

                    }

                }

                pixels[row * width + col] = (int) pixel;

            }

        }

        double end = now_ms();

        double delta = end - start;

        __android_log_print(ANDROID_LOG_VERBOSE, APPNAME, "%f", delta);

    }

    pthread_exit(0);

}

安卓.mk

(应该放在Android项目根目录下的jni文件夹中)

LOCAL_PATH := $(call my-dir)
MY_PATH := $(LOCAL_PATH)
include $(call all-subdir-makefiles)

include $(CLEAR_VARS)

LOCAL_PATH := $(MY_PATH)

LOCAL_MODULE    := native
LOCAL_LDLIBS := -llog
LOCAL_SRC_FILES := native.c

include $(BUILD_SHARED_LIBRARY)

总结

代码成本降低了约 20-30%，可变性降低了一个数量级。

代码是通过在根文件夹(可在此处找到:http://developer.android.com/tools/sdk/ndk/index.html)中从 Android 提供的 NDK 库执行 ndk-build 命令编译的。

结果

Nexus 4(毫秒):

01-14 13:41:21.132: V/DELTA(23679): 56.554199
01-14 13:41:21.192: V/DELTA(23679): 58.568604
01-14 13:41:21.252: V/DELTA(23679): 59.484131
01-14 13:41:21.302: V/DELTA(23679): 56.768066
01-14 13:41:21.362: V/DELTA(23679): 54.692383
01-14 13:41:21.412: V/DELTA(23679): 51.823730
01-14 13:41:21.472: V/DELTA(23679): 55.668945
01-14 13:41:21.522: V/DELTA(23679): 56.920654
01-14 13:41:21.582: V/DELTA(23679): 56.371094
01-14 13:41:21.642: V/DELTA(23679): 58.507568
01-14 13:41:21.702: V/DELTA(23679): 59.697754
01-14 13:41:21.752: V/DELTA(23679): 53.990723
01-14 13:41:21.812: V/DELTA(23679): 55.669189

Nexus 7(毫秒):

01-14 13:41:25.685: V/DELTA(2916): 65.867920
01-14 13:41:25.745: V/DELTA(2916): 65.986816
01-14 13:41:25.815: V/DELTA(2916): 66.685059
01-14 13:41:25.885: V/DELTA(2916): 67.033936
01-14 13:41:25.945: V/DELTA(2916): 65.703857
01-14 13:41:26.015: V/DELTA(2916): 66.653076
01-14 13:41:26.085: V/DELTA(2916): 66.922119
01-14 13:41:26.145: V/DELTA(2916): 67.030029
01-14 13:41:26.215: V/DELTA(2916): 67.014893
01-14 13:41:26.285: V/DELTA(2916): 67.034912
01-14 13:41:26.345: V/DELTA(2916): 67.089844
01-14 13:41:26.415: V/DELTA(2916): 65.860107
01-14 13:41:26.485: V/DELTA(2916): 65.642090
01-14 13:41:26.545: V/DELTA(2916): 65.574951
01-14 13:41:26.615: V/DELTA(2916): 65.991943

关于android - 在 Nexus 4 上进行计算量大的数组处理时，会出现周期性的性能峰值是什么原因造成的？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/14299288/

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