在分析內存優化的過程中，其中一個最重要的是我們如何查看cpu的占用率和內存的占用率呢，這在一定程度上很重要，經過查詢資料，研究了一下，暫時了解到大概有以下幾種方式，如果哪位高手有更好的辦法，或者文中描述有錯誤，還望高手在下面留言，非常感謝！
一、 通過eclipse，ADT開發工具的DDMS來查看(Heap)
在“Devices”窗口中選擇模擬器中的一個需要查看的程序，從工具條中選“Update heap”按鈕，給這個程序設置上“heap Updates”，然后在Heap視圖中點擊Cause GC就可以實時顯示這個程序的一些內存和cpu的使用情況了。
然后就會出現如下界面：
說明：
a) 點擊“Cause GC”按鈕相當於向虛擬機請求了一次gc操作；
b) 當內存使用信息第一次顯示以后，無須再不斷的點擊“Cause GC”，Heap視圖界面會定時刷新，在對應用的不斷的操作過程中就可以看到內存使用的變化；
c) 內存使用信息的各項參數根據名稱即可知道其意思，在此不再贅述。
大致解析如下：
這個就是當前應用的內存占用，allocated 是已經分配的內存 free是空閑內存，
heap size 是虛擬機分配的 不是固定值
heap size 的最大值跟手機相關的
有網友說，
一般看1byte的大部分就是圖片占用的
如何判斷應用是否有內存泄漏的可能性呢？
如何才能知道我們的程序是否有內存泄漏的可能性呢。這里需要注意一個值：Heap視圖中部有一個Type叫做data object，即數據對象，也就是我們的程序中大量存在的類類型的對象。在data object一行中有一列是“Total Size”，其值就是當前進程中所有Java數據對象的內存總量，一般情況下，這個值的大小決定了是否會有內存泄漏。可以這樣判斷：
a) 不斷的操作當前應用，同時注意觀察data object的Total Size值；
b) 正常情況下Total Size值都會穩定在一個有限的范圍內，也就是說由於程序中的的代碼良好，沒有造成對象不被垃圾回收的情況，所以說雖然我們不斷的操作會不斷的生成很多對 象，而在虛擬機不斷的進行GC的過程中，這些對象都被回收了，內存占用量會會落到一個穩定的水平；
c) 反之如果代碼中存在沒有釋放對象引用的情況，則data object的Total Size值在每次GC后不會有明顯的回落，隨着操作次數的增多Total Size的值會越來越大，
直到到達一個上限后導致進程被kill掉。
d) 此處已system_process進程為例，在我的測試環境中system_process進程所占用的內存的data object的Total Size正常情況下會穩定在2.2~2.8之間，而當其值超過3.55后進程就會被kill。
在如下的位置：
二、通過linux命令來查看
常用的命令有
adb shell
ps 是看進程的
top命令是看占用率的
3.獲取最大內存的方法
ActivityManager am = (ActivityManager) getSystemService(Context.ACTIVITY_SERVICE);
am.getMemoryClass();
這個是最大內存，如果超過這個內存就OOM了
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內存耗用：VSS/RSS/PSS/USS 的介紹
- VSS - Virtual Set Size 虛擬耗用內存（包含共享庫占用的內存）
- RSS - Resident Set Size 實際使用物理內存（包含共享庫占用的內存）
- PSS - Proportional Set Size 實際使用的物理內存（比例分配共享庫占用的內存）
- USS - Unique Set Size 進程獨自占用的物理內存（不包含共享庫占用的內存）
一般來說內存占用大小有如下規律：VSS >= RSS >= PSS >= USS
The aim of this post is to provide information that will assist in interpreting memory reports from various tools so the true memory usage for Linux processes and the system can be determined.
Android has a tool called procrank (/system/xbin/procrank), which lists out the memory usage of Linux processes in order from highest to lowest usage. The sizes reported per process are VSS, RSS, PSS, and USS.
For the sake of simplicity in this description, memory will be expressed in terms of pages, rather than bytes. Linux systems like ours manage memory in 4096 byte pages at the lowest level.
VSS (reported as VSZ from ps) is the total accessible address space of a process. This size also includes memory that may not be resident in RAM like mallocs that have been allocated but not written to. VSS is of very little use for determing real memory usage of a process.
RSS is the total memory actually held in RAM for a process. RSS can be misleading, because it reports the total all of the shared libraries that the process uses, even though a shared library is only loaded into memory once regardless of how many processes use it. RSS is not an accurate representation of the memory usage for a single process.
PSS differs from RSS in that it reports the proportional size of its shared libraries, i.e. if three processes all use a shared library that has 30 pages, that library will only contribute 10 pages to the PSS that is reported for each of the three processes. PSS is a very useful number because when the PSS for all processes in the system are summed together, that is a good representation for the total memory usage in the system. When a process is killed, the shared libraries that contributed to its PSS will be proportionally distributed to the PSS totals for the remaining processes still using that library. In this way PSS can be slightly misleading, because when a process is killed, PSS does not accurately represent the memory returned to the overall system.
USS is the total private memory for a process, i.e. that memory that is completely unique to that process. USS is an extremely useful number because it indicates the true incremental cost of running a particular process. When a process is killed, the USS is the total memory that is actually returned to the system. USS is the best number to watch when initially suspicious of memory leaks in a process.
For systems that have Python available, there is also a nice tool called smem that will report memory statistics including all of these categories.
# procrank
procrank
PID Vss Rss Pss Uss cmdline
481 31536K 30936K 14337K 9956K system_server
475 26128K 26128K 10046K 5992K zygote
526 25108K 25108K 9225K 5384K android.process.acore
523 22388K 22388K 7166K 3432K com.android.phone
574 21632K 21632K 6109K 2468K com.android.settings
521 20816K 20816K 6050K 2776K jp.co.omronsoft.openwnn
474 3304K 3304K 1097K 624K /system/bin/mediaserver
37 304K 304K 289K 288K /sbin/adbd
29 720K 720K 261K 212K /system/bin/rild
601 412K 412K 225K 216K procrank
1 204K 204K 185K 184K /init
35 388K 388K 182K 172K /system/bin/qemud
284 384K 384K 160K 148K top
27 376K 376K 148K 136K /system/bin/vold
261 332K 332K 123K 112K logcat
33 396K 396K 105K 80K /system/bin/keystore
32 316K 316K 100K 88K /system/bin/installd
269 328K 328K 95K 72K /system/bin/sh
26 280K 280K 93K 84K /system/bin/servicemanager
45 304K 304K 91K 80K /system/bin/qemu-props
34 324K 324K 91K 68K /system/bin/sh
260 324K 324K 91K 68K /system/bin/sh
600 324K 324K 91K 68K /system/bin/sh
25 308K 308K 88K 68K /system/bin/sh
28 232K 232K 67K 60K /system/bin/debuggerd
#