Floating-point Numbers are not real Numbers.
浮点数并不是实数。
The same is not true for floating-point numbers.
但浮点数则不是这样。
Note that floating-point multiplication doesn't have these issues.
注意浮点乘法没有这样的问题。
Floating-point instructions and decimal floating-point instructions.
浮点指令和十进制浮点指令。
It also has the first decimal floating-point unit integrated in silicon.
它还首次在芯片中集成了十进制浮点单元。
For example, the C programming language has integer and floating-point types.
例如，c编程语言具有整型和浮点类型。
These workloads heavily use either the floating-point units or the memory bandwidth.
这些工作负荷会占用大量的浮点单元或内存带宽。
There are differences in the definition of floating-point Numbers and long variable types.
浮点型数字和长变量类型的定义是有差异的。
Likewise, floating-point values are passed through the floating-point registers 1 through 13.
同理，浮点值是通过浮点寄存器1到13传递的。
Calculations that require strict floating-point semantics should be handled on the server side.
需要严格遵守浮点语义学的计算应当在服务器端处理。
If you want to force a floating-point result, be sure that at least one of the operands is a floating-point type.
如果要强制取得浮点结果，则必须确保操作数中至少有一个为浮点类型。
Even under version 7.2, Vim does only floating-point arithmetic if one of the operands is explicitly floating-point.
即使对于版本7.2，如果其中一个运算对象被明确声明为浮点类型，那么Vim只支持浮点算术。
The standard mathematical operators, +, -, /, * are supported on both integer and floating point values, and you can mix and match floating-point and integers in calculations.
在整数和浮点数上，都支持使用标准的数学操作符（+、-、/ 和 *），可以在算式中混合使用浮点数和整数。
Remember, integer arithmetic is much faster than floating-point arithmetic, as it can usually be done directly by the processor, rather than relying on external FPUs or floating point math libraries.
记住，整形数运算要比浮点数运算快得多，因为处理器可以直接进行整型数运算，浮点数运算需要依赖于外部的浮点数处理器或者浮点数数学库。
Float: a floating point number.
浮点数：一个浮点数。
Floating point Numbers are not exact, and manipulating them will result in rounding errors.
浮点数不是精确值，所以使用它们会导致舍入误差。
An attempt was made to execute a floating point instruction when the floating point available bit in the MSR (machine status register) was disabled.
如果在MSR(机器状态寄存器)中可用的浮点位被禁用，将尝试执行一个浮点指令。
You can read integer, floating point, and string values that are all defined as' scalar 'objects.
您可以读取被定义为“标量”的整型、浮点型和字符串值。
So both of these stories involve floating point values, but only in this case am I actually allocating memory.
所以这两个故事都涉及到浮点类型，但是只有那样我们才能真正地分配到内存。
One of the trickiest checks in regression setups is doing floating point comparisons.
回归测试中最棘手的检查之一是浮点比较。
Why do you need separate macros for floating point comparisons?
为什么需要用单独的宏进行浮点数比较？
Floating point is a very similar concept, except that computers use binary rather than decimal as their base.
浮点是一个非常类似的概念，除了计算机使用二进制而不是十进制作为基础。
It lacked floating point and parallel processing ability.
它缺少浮点和并行处理功能。
Floating point and decimal Numbers are not nearly as well-behaved as integers, and you cannot assume that floating point calculations that "should" have integer or exact results actually do.
浮点数和小数不象整数一样“循规蹈矩”，不能假定浮点计算一定产生整型或精确的结果，虽然它们的确“应该”那样做。
Those topics deal with floating point and vector processing and are outside the scope of this article.
这些主题涉及的是浮点和向量处理，已经超出了本文的范围。
Operations for floating point variables are limited to simple assignment expressions and as arguments to VUE functions.
对于浮点变量的操作只限于简单的赋值表达式和作为VUE函数的变量。
If you're reading a floating point number, there are other concerns.
如果您读取的浮点数，还有另外需要关注的问题。
It had separate floating point registers and could scale from the low - to the high-end workstations.
它有单独的浮点寄存器，可以从低端工作站扩展到高端工作站。
Floating point arithmetic is rarely exact.
浮点运算很少是精确的。
Floating point arithmetic is rarely exact.
浮点运算很少是精确的。
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