如果我们回想一下我们一开始讲过的数据对象的种类，浮点数，整数，字符串，它们实际上有相同的行为方式。
If we go back up to the kinds of data objects we started with, floats, ints, strings, they actually behave the same way.
注意浮点乘法没有这样的问题。
Note that floating-point multiplication doesn't have these issues.
ieee浮点值的格式如图1所示。
The layout of IEEE floating point values is shown in Figure 1.
它缺少浮点和并行处理功能。
2比特的浮点型数据精度更大。
注意纵横比和剪贴板的值应为浮点值。
Notice that the aspect ratio and the values for the clipping planes are float values.
为什么需要用单独的宏进行浮点数比较？
Why do you need separate macros for floating point comparisons?
例如，c编程语言具有整型和浮点类型。
For example, the C programming language has integer and floating-point types.
不要用浮点值表示精确值。
还可以使用指数表示浮点数，参见清单8。
Floats can also be expressed using exponents, as shown Listing 8.
回归测试中最棘手的检查之一是浮点比较。
One of the trickiest checks in regression setups is doing floating point comparisons.
它还首次在芯片中集成了十进制浮点单元。
It also has the first decimal floating-point unit integrated in silicon.
浮点型数字和长变量类型的定义是有差异的。
There are differences in the definition of floating-point Numbers and long variable types.
简单类型包括字符串、浮点数、整数、枚举等。
Simple types include string, float, integer, enumeration, etc.
根据IEEE浮点标准，它只是值的文本表示。
It is simply a textual representation of the value according to the IEEE floating point standard.
浮点数并不是实数。
这些工作负荷会占用大量的浮点单元或内存带宽。
These workloads heavily use either the floating-point units or the memory bandwidth.
浮点指令和十进制浮点指令。
Floating-point instructions and decimal floating-point instructions.
坐标值是数字(小数、浮点数等)，不是字符串。
The coordinate values are numeric (decimal, float, etc.), not character strings.
随着数字变大，它们之间的浮点数就会越来越少。
浮点数不是精确值，所以使用它们会导致舍入误差。
Floating point Numbers are not exact, and manipulating them will result in rounding errors.
当内核在执行浮点指令时，FPU状态不被保存。
When the kernel is executing floating point instructions, the FPU state is not saved.
在未来的文章中，我计划仔细研究一下浮点工作负载。
In future articles, I plan to take a closer look at floating point workloads.
需要严格遵守浮点语义学的计算应当在服务器端处理。
Calculations that require strict floating-point semantics should be handled on the server side.
您可以读取被定义为“标量”的整型、浮点型和字符串值。
You can read integer, floating point, and string values that are all defined as' scalar 'objects.
同理，浮点值是通过浮点寄存器1到13传递的。
Likewise, floating-point values are passed through the floating-point registers 1 through 13.
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。
Those topics deal with floating point and vector processing and are outside the scope of this article.
支持的变量包括整型、浮点型的数字、字符串、数组和对象。
Supported variables include integers, floating point Numbers, strings, arrays, and objects.
当然，这并不总是可能的，但您应该意识到要限制浮点数比较。
This is, of course, not always possible, but you should be aware of the limitations of floating point comparison.
这些类允许各种几何图形建立在双精度或浮点精度的坐标系上。
These classes allow the various geometric shapes to be constructed with coordinates of either double or float precision.
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