case/casez/casex 的区分与使用
参考:http://www.cnblogs.com/poiu-elab/archive/2012/11/02/2751323.html
与 verilog数字系统设计基础
一般来说,使用最多的是CASE语句,casez和casex基本上很少使用,不过因为它们的功能强大,不能不学会它的使用。
一般性的常识是使用casez,强烈的建议不要使用casex。首先要明确的是'?'代表的不是don't care,而是'z'。再有就是case/casez/casex其实都是可综合的,这一点也要记住。
区分:
case语句的表达式的值有4中情况:0、1、z、x。4种是不同的,故表达式要严格的相等才可以操作分支语句。
casez语句中的表达式情况有三种:0、1、x。不用关心z,z可以和任何数值相等,即z =0.z= 1,z=x;
casex语句的表达式情况有二种:0、1.不用关心x和z。即x=z=0,x=z=1.
另外表达式的值是按从上到下的顺序来与分支条件的比较,如果相等,则不再与下面的分支相比较而直接执行该分支的语句。
实例分析看不同:
一、simulation difference
1、先看case
case (sel)
2'b00: y = a;
2'b01: y = b;
2'bx0: y = c;
2'b1x: y = d;
2'bz0: y = e;
2'b1?: y = f;
default : y = g;
endcase
不同的sel,对应
Result:
sel y case item
00 a 00
11 g default
xx g default
x0 c x0
1z f 1?
z1 g default
为啥呢?就是因为case会认出每种情况,1/0/z/x,所以就得到了上面的结果。很是严格。
2. casez,就是会把z/?匹配成任意,也会把任意匹配成z/?的。
casez (sel)
2'b00: y = a;
2'b01: y = b;
2'bx0: y = c;
2'b1x: y = d;
2'bz0: y = e;
2'b1?: y = f;
default: y = g;
endcase
对应的
Result:
sel y case item
00 a 00
11 f 1?
xx g default
x0 c x0 (would have matched with z0(item 5) if item 3 is not present.)
1z d 1x (would have matched with z0(item 5) & 1?(item 6) also.)
z1 b 01 (would have matched with 1?(item 6) also.)
首先,case的描述,匹配都是从上到下进行的,如果使用了casez,看上面的casez的列表,只要输入有z/?的话,就能和任意匹配,只要列表的index项有z/?,就能匹配任意项,再对照上面的例子,就明了了。
3、casex呢,再来
casex (sel)
2'b00 : y = a;
2'b01 : y = b;
2'bx0 : y = c;
2'b1x : y = d;
2'bz0 : y = e;
2'b1? : y = f;
default : y = g;
endcase
结果呢?
Result:
sel y case item
00 a 00
11 d 1x (would have matched with 1? also)
xx a 00 (would have matched with 1? also)
x0 a 00 (would have matched with all items except 01)
1z c x0 (would have matched with all items except 00,01)
z1 b 01 (would have matched with 1x, 1? also)
还是一样的道理,casex也是从上到下匹配,当出现x/z/?的输入的时候,都不会care,只管不是大大情况来匹配,上面的解释也是很容易看懂。就不多说了。
二、synthesis difference
综合的时候又是另一番景象了,因为综合工具其实都不会管你什么x/z/?之类的,他能认识什么呢?让我们再来测试一下,case/casez/casex不同写法的综合结果,例子都是同样的
1、例子1
case (sel)
2'b00 : mux_out = mux_in[0];
2'b01 : mux_out = mux_in[1];
2'b1? : mux_out = mux_in[2];
default : mux_out = mux_in[3];
endcase
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" 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" 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" alt="" width="312" height="194" />
2、例子2
case (sel)
2'b00 : mux_out = mux_in[0];
2'b01 : mux_out = mux_in[1];
2'b1x : mux_out = mux_in[2];
default : mux_out = mux_in[3];
endcase
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" 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" 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" alt="" width="287" height="186" />
通过上面两个例子我们得到的结论是:
1. Case statement will not consider for synthesis, the items containing x or z.
2. Casez and Casex will give the same output after synthesis, treating both x, z in case items as dont cares.
就是说你的case(不是casez/casex的时候)的index列表里面的x和z,都被综合工具认为是不可达到的状态就被去掉了。
casez和casex里面的x/z都被认为是don't care,所以综合出的电路会是一致的。
三、simulation vs synthesis
例子
casez (sel)
2'b00 : mux_out = mux_in[0];
2'b01 : mux_out = mux_in[1];
2'b1? : mux_out = mux_in[2];
default : mux_out = mux_in[3];
endcase
再看simulation与synthesis的结果
+---+-----------------------------------+-----------------------------------+
| | casez | casex |
|sel| Pre-synthesis Post-synthesis | Pre-synthesis Post-synthesis |
+---+-----------------------------------+-----------------------------------+
|xx | mux_in[3] x | mux_in[0] x |
|1x | mux_in[2] mux_in[2] | mux_in[2] mux_in[2] |
|0x | mux_in[3] x | mux_in[0] x |
|zz | mux_in[0] x | mux_in[0] x |
|1z | mux_in[2] mux_in[2] | mux_in[2] mux_in[2] |
|0z | mux_in[0] x | mux_in[0] x |
+---+-----------------------------------+-----------------------------------+
作者此时说了两句话就是Another interesting, very important observation is that when ever there is a mismatch, post-synthesis result will become x. During RTL simulation if sel becomes xx, casez executes default statement(which is the intended behaviour) but casex executes case item1 (which is not the intended behaviour), clearly a mismatch.
看上面的表这就能说明问题了,不管用casez还是casex,simulation和synthesis的结果都会有出入的,所以在写代码的时候,考虑到综合,casez与casex都是完全等同的了,就不必要非得纠结写哪个比较好了。
或许casez有那么一点好处,能体现在
casez (sel)
000: y = a;
001: y = b;
01?: y = c;
1??: y = d;
endcase
这样的代码,如果用case写的话
case (sel)
000 : y = a;
001 : y = b;
010,011 : y = c;
100,101,110,111 : y = d;
endcase
就是这点有点罢了~
四、summary
1、我们在写代码的时候如果用了case,那么就不要在index列表里面出现x/z/?,综合工具认不出这些,都会当做don't care
2、casez和casex综合的结果是一致的。
3、casez稍好用一些,因为它可以用来代表don't care的值
4、最重要的一点就是,casez和casex其实没有孰优孰劣
就这样,以后我用的时候没准会更多的用casez,case其实也是好东西,最好弄明白了自己真正要表达的意思是什么再动手写代码,还要深刻理解case/casez/casex到底起到的什么作用~
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