这舍入误差的特征是浮点计算。
This rounding error is the characteristic feature of floating-point computation.
二元代表性浮点值影响的精密度和准确度的浮点计算。
Binary representation of floating-point values affects the precision and accuracy of floating-point calculations.
因此浮点计算的结果必须经常圆为了适应回其有限表示。
Therefore the result of a floating-point calculation must often be rounded in order to fit back into its finite representation.
默认情况下，编译器使用协处理器的80位寄存器保存浮点计算的中间结果。
By default, the compiler USES the coprocessor's 80-bit registers to hold the intermediate results of floating-point calculations.
这些系统的整数计算性能比其他所有机器都出色，还把浮点计算性能提高了10倍。
The unique factor of these systems were that they outperformed all other machines in integer-compute performance and also by a factor of 10 in floating-point performance.
目前的积分是基于处理器的实际浮点计算量相对于基准测试结果所耗费的时间来评定的。
Credits are now based upon the actual number of floating point operations done rather than by multiplying the benchmark results by the time taken.
在我们期待喷气发动机组件、飞行汽车、浮点计算机和宇宙飞船问世的同时，这一年仍然算是令人激动的科技之年。
While we were supposed to have jet packs, flying cars, floating computers and spaceships, this was still a pretty amazing year for technology.
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。
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.
相对于浮点计算法，移位-加操作最大的优点是计算简单，特别易于超大规模集成电路实现，因而使硬件实时处理图像信号成为可能。
Compared with the floating-point computing method, the shift-add operation is simpler, and can be implemented easily by VLSI, which enables the real-time image processing to be realized by hardware.
处理器将数据流解释为要执行的指令，它拥有一个或多个处理单元，用于执行整数和浮点运算以及更高级的计算。
A processor interprets a stream of data as instructions to execute; it has one or more processing units that perform integer and floating-point arithmetic as well as more advanced computations.
最后我们发现无法使用浮点处理器直接计算超函数（结果使用软件实现了）...
Oh, and the fact that you can't use the floating point processor directly to calculate transcendental functions (it's done in software instead).
由有限精度浮点数字引起的很小的舍入错误就会严重歪曲数学精度计算。
Mathematically precise calculations can be thrown severely askew by small round-off errors caused by finite-precision floating-point Numbers.
最好将浮点运算保留用作计算本来就不精确的数值，譬如测量。
It is best to reserve the use of floating point arithmetic for calculations that involve fundamentally inexact values, such as measurements.
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。
Floating point is a very similar concept, except that computers use binary rather than decimal as their base.
如果任意一个操作数是浮点型的，则所有操作数都将按浮点型进行计算，并且结果也是浮点型的。
If any of the operands is a float, then all operands are evaluated as floats, and the results are floats.
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.
区别在于一个事实：计算机中使用的浮点数据类型无法包含每个实数。
The difference lies in the fact that floating-point data types used in computers can't hold every real number.
所以这里的意思是编译器将,做“计算“，譬如13这样一个浮点数,-到另一个浮点数-,然后为我们处理除法。
So what that means is the compiler is actually going to first "cast" so to speak 13 from whatever it is - to a float -- to a floating point value -- and then perform the division for us.
注意，在本例中，sum必须被初始化为一个显式的浮点值；否则，所有后续计算都将使用整数运算计算。
Note that, in this example, sum must be initialized to an explicit floating-point value; otherwise, all the subsequent computations will be done using integer arithmetic.
这里我的确需要告诉计算机，“给我一些字节内存，来存储一个值，那个值将是，浮点型的数值。”
Here I actually need to tell the computer, "Give me some bytes in ram in which to store a value, and that value's going to be a floating point value."
当代码被编译或者解释运行时，“0.1”已经被近似转化为这种形式下最接近的一个浮点数，这导致在计算还没有真正开始之前，一个微小的舍入误差就已经存在了。
When the code is compiled or interpreted, your "0.1" is already rounded to the nearest number in that format, which results in a small rounding error even before the calculation happens.
我们增加了一些新的API调用，允许计算程序进行自己的CPU测试，或者直接报告它们的浮点操作数目。
We have added new API calls that allow applications to do their own CPU benchmarking, or directly report their floating-point operation count.
浮点数表示法，含部份换轴之高斯消去法，使用矩阵大小之计算尺度调整，带状及三角对角系统，LU分解。
Floating point representation, Gaussian elimination with partial pivoting, scaling of computations with matrix size, banded and tri-diagonal systems, LU decomposition.
因为在内部，计算机使用一种非精确的(二进制浮点数)形式表示诸如0.1,0.2,0.3之类的小数。
Because internally, computers use a format (binary floating-point) that cannot accurately represent a number like 0.1, 0.2 or 0.3 at all.
该文基于语音识别在缺乏浮点运算能力的嵌入式系统上的实现，给出了一种快速高斯计算的新方法。
This paper proposes a new approach for fast gaussian computing based on the embedded speech-recognition implementation lacking of float-point computation ability.
指示对象是否包含不精确计算，如浮点运算。
Indicates whether the object contains an imprecise computation, such as floating point operations.
对计算机浮点数算术运算的舍入误差进行分析，是对数值计算方法作误差分析的基础。
To analyze the rounding error of calculator floating-point Numbers arithmetic operation is the foundation of numerical calculation method's error analysis.
采用浮点数编码对模糊控制规则进行优化，既提高了运算效率和计算精度，又保证了控制系统的快速性和全局最优性。
Floating-point coding is adopted to optimize fuzzy control rules, it can improve the efficiency and accuracy of calculation, also can guarantee fastness and global optimal.
将缩放浮点值十在计算过程中保持精度总是精确的？
Would scaling a float value by ten to preserve precision during a calculation be always precise?
将缩放浮点值十在计算过程中保持精度总是精确的？
Would scaling a float value by ten to preserve precision during a calculation be always precise?
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