Android提供了一个名为meminfo的小工具帮助应用分析自身的内存占用，并且在4.4还新增了memtrack HAL模块，SoC厂商通过实现memtrack模块，让meminfo可以获取GPU相关的一些内存分配状况。了解meminfo的实现，对我们更深入 了解应用的内存占用状况是很有帮助的。而这篇文章的目的就是分析Android 4.4 meminfo的内部实现源码，让开发者通过这些信息可以更了解自己应用的内存占用状况。
在控制台输入命令”adb shell dumpsys meminfo YOUR-PACKAGE-NAME”，可以看到类似下图的结果：
** MEMINFO in pid 14120[com.UCMobile.test]**PssPrivatePrivateSwappedHeapHeapHeapTotalDirtyCleanDirtySizeAllocFree------------------------------------------NativeHeap1878861878720032523217409338594DalvikHeap24801244440041476358995577DalvikOther70070000Stack50850800Other dev 335643260040.so mmap 9019124472680.apk mmap 1010160.ttf mmap 133006960.dex mmap 2248022480 code mmap 98501880 image mmap 1182908120Other mmap 13041080Graphics255042550400 GL 2196219600Unknown324763247600 TOTAL 32263030845610540036670820999244171
实际的调用代码入口在android.os.Debug.java和对应的CPP文件 android_os_Debug.cpp，Debug.java的getMeminfo方法实际上调用了android_os_Debug.cpp的 android_os_Debug_getDirtyPagesPid方法。
staticvoid android_os_Debug_getDirtyPagesPid(JNIEnv*env, jobject clazz, jint pid, jobject object){stats_t stats[_NUM_HEAP]; memset(&stats,0,sizeof(stats)); load_maps(pid, stats);struct graphics_memory_pss graphics_mem;if(read_memtrack_memory(pid,&graphics_mem)==0){...}...}staticvoid load_maps(int pid,stats_t* stats){char tmp[128]; FILE *fp; sprintf(tmp,"/proc/%d/smaps", pid); fp = fopen(tmp,"r");if(fp ==0)return; read_mapinfo(fp, stats); fclose(fp);}
从上面的代码可以看到，android_os_Debug_getDirtyPagesPid方法先调用了load_maps方法，而 load_maps方法要做的事情也很简单，它打开/proc/PID/smaps虚拟文件，读取里面的信息，在已ROOT的设备上，我们可以通过 “adb shell cat /proce/PID/smaps”直接将这个虚拟文件的信息打印在控制台上。
80ff5000-810f2000 rw-p 0000000000:000[stack:12211]Size:1012 kB Rss:4 kB Pss:4 kB ...81100000-811a4000 rw-s 000f400000:0b6285/dev/kgsl-3d0Size:656 kB Rss:652 kB Pss:352 kB ...811d1000-811e0000 rw-p 0000000000:000[anon:libc_malloc]Size:60 kB Rss:60 kB Pss:60 kB ...Name:[anon:libc_malloc]
“adb shell cat /proce/PID/smaps”输出的信息如上图所示，它实际上是应用的userspace地址空间的内存分配表，记录了应用分配的每一块内存的地 址，类别，大小等信息，而load_maps方法调用read_mapinfo方法从这个表里面读出每一块内存的分配信息，分类进行累加，得出 Native Heap，Dalvik Heap等各个类别的内存占用。
但是应用所使用的全部内存里面，有一些内存块是不映射到进程的userspace地址空间的（主要是GPU所使用的内存），这些内存块的信息在 smaps里面无法找到，所以在Android 4.4里面新增了一个memtrack的HAL模块由SoC厂商实现，如果SoC厂商实现了memtrack模块，meminfo则可以通过 libmemtrack的调用获取一些跟GPU相关的内存使用信息。所以我们看到android_os_Debug_getDirtyPagesPid方 法通过调用read_memtrack_memory方法来读取Graphics，GL这两项的内存使用信息。
/* * Uses libmemtrack to retrieve graphics memory that the process is using. * Any graphics memory reported in /proc/pid/smaps is not included here. */staticint read_memtrack_memory(struct memtrack_proc* p,int pid,struct graphics_memory_pss* graphics_mem){int err = memtrack_proc_get(p, pid);...ssize_t pss = memtrack_proc_graphics_pss(p);... graphics_mem->graphics = pss /1024; pss = memtrack_proc_gl_pss(p);... graphics_mem->gl = pss /1024; pss = memtrack_proc_other_pss(p);... graphics_mem->other = pss /1024;return0;}
read_memtrack_memory方法的实现如上图所示，它读取了Graphics，GL，Other这三类内存信息，而这三个类别的定义在hardware/memtrack.h里面。
/* * The Memory Tracker HAL is designed to return information about device-specific * memory usage. The primary goal is to be able to track memory that is not * trackable in any other way, for example texture memory that is allocated by * a process, but not mapped in to that process' address space. * A secondary goal is to be able to categorize memory used by a process into * GL, graphics, etc. All memory sizes should be in real memory usage, * accounting for stride, bit depth, rounding up to page size, etc. * * A process collecting memory statistics will call getMemory for each * combination of pid and memory type. For each memory type that it recognizes * the HAL should fill out an array of memtrack_record structures breaking * down the statistics of that memory type as much as possible. For example, * getMemory(, MEMTRACK_TYPE_GL) might return: * { { 4096, ACCOUNTED | PRIVATE | SYSTEM }, * { 40960, UNACCOUNTED | PRIVATE | SYSTEM }, * { 8192, ACCOUNTED | PRIVATE | DEDICATED }, * { 8192, UNACCOUNTED | PRIVATE | DEDICATED } } * If the HAL could not differentiate between SYSTEM and DEDICATED memory, it * could return: * { { 12288, ACCOUNTED | PRIVATE }, * { 49152, UNACCOUNTED | PRIVATE } } * * Memory should not overlap between types. For example, a graphics buffer * that has been mapped into the GPU as a surface should show up when * MEMTRACK_TYPE_GRAPHICS is requested, and not when MEMTRACK_TYPE_GL * is requested. */enum memtrack_type { MEMTRACK_TYPE_OTHER =0, MEMTRACK_TYPE_GL =1, MEMTRACK_TYPE_GRAPHICS =2, MEMTRACK_TYPE_MULTIMEDIA =3, MEMTRACK_TYPE_CAMERA =4, MEMTRACK_NUM_TYPES,};
Graphics对应了MEMTRACK_TYPE_GRAPHICS，GL对应了MEMTRACK_TYPE_GL，而Other实际上是 MEMTRACK_TYPE_OTHER，MEMTRACK_TYPE_MULTIMEDIA，MEMTRACK_TYPE_CAMERA这三项之和。 memtrack是由SoC厂商实现的，在AOSP的源码里面我们可以找到高通的实现源码，在msm8974/libmemtrack/kgsl.c里 面。
int kgsl_memtrack_get_memory(pid_t pid,enum memtrack_type type,struct memtrack_record *records,size_t*num_records){... sprintf(tmp,"/d/kgsl/proc/%d/mem", pid); fp = fopen(tmp,"r");...if(type == MEMTRACK_TYPE_GL){ sprintf(tmp,"/proc/%d/smaps", pid); smaps_fp = fopen(tmp,"r");...}while(1){unsignedlong uaddr;unsignedlong size;char line_type[7];int ret;if(fgets(line,sizeof(line), fp)== NULL){break;}/* Format: * gpuaddr useraddr size id flags type usage sglen * 545ba000 545ba000 4096 1 ----p gpumem arraybuffer 1 */ ret = sscanf(line,"%*x %lx %lu %*d %*s %6s %*s %*d\n",&uaddr,&size, line_type);if(ret !=3){continue;}if(type == MEMTRACK_TYPE_GL && strcmp(line_type,"gpumem")==0){bool accounted =false;/* * We need to cross reference the user address against smaps, * luckily both are sorted. */while(smaps_addr <= uaddr){unsignedlong start;unsignedlongend;unsignedlong smaps_size;if(fgets(line,sizeof(line), smaps_fp)== NULL){break;}if(sscanf(line,"%8lx-%8lx",&start,&end)==2){ smaps_addr = start;continue;}if(smaps_addr != uaddr){continue;}if(sscanf(line,"Rss: %lu kB",&smaps_size)==1){if(smaps_size){ accounted =true; accounted_size += size;break;}}}if(!accounted){ unaccounted_size += size;}}elseif(type == MEMTRACK_TYPE_GRAPHICS && strcmp(line_type,"ion")==0){ unaccounted_size += size;}}...}
kgsl_memtrack_get_memory是memtrack的getMemory方法的具体实现，我们可以看到它实际上是读取一张内部的 GPU内存分配表的信息（虚拟文件/d/kgsl/proc/PID/mem），在已ROOT的设备上，我们可以通过“adb shell cat /d/kgsl/proc/PID/mem”将这张内存分配表的信息打印到控制台上，如下图所示：
gpuaddr useraddr size id flags type usage sglen 7565e0000000000040961----p gpumem arraybuffer 1756bc00000000000655362-r--p gpumem command 16756cd00000000000655363-r--p gpumem command 16756de00000000000655364-r--p gpumem command 16756fb0000000000040965----p gpumem gl 175fe2000000000002621446----p gpumem gl 64760230000000000081927----p gpumem gl 2760260000000000081928----p gpumem gl 2760290000000000040969----p gpumem texture 1...94d7100000000000131072362----p gpumem vertexarraybuff 3294da000000000000667648176--l-p gpumem texture 16394e4400000000000131072363----p gpumem any(0)3294e6500000000000131072364----p gpumem any(0)32 c0000000 000000001726873631--L-- ion egl_image 4216 c1100000 00000000825753636--L-- ion egl_surface 21 c1900000 000000008257536164--L-- ion egl_surface 21 c2100000 000000008257536175--L-- ion egl_surface 21
其中ion类型（由ION内存分配器分配的内存）的内存块统计到Graphics类别里面，从上图我们可以看到有三块egl_surface，它们 对应应用所使用的窗口的三个Buffer，还有一个egl_image暂时不清楚用途，这些都是应用启动后Android自动分配的。gpumem类型的 内存块统计到GL类别里面，包括GL里面的纹理（texture），各种shader，vertex buffer等等。另外，因为有些内存块映射到了userspace，有些则没有映射，所以映射到userspace的内存块会被标记为 accounted，避免meminfo重复计数，meminfo最终显示的Graphics和GL的内存值是哪些没有映射到userspace的内存块 的大小之和。