Unverified50% confidenceFactExact time
Double-precision floating-point (double, 64-bit) can precisely represent integers within the range of ±2^53, but still cannot cover the full range of 64-bit integer division.
1
Sources
50%
Confidence
Long-term
Relevance
8/19/2026
First Seen
Sources
整数除法转浮点除法：反直觉的CPU性能优化技巧详解
Related Claims
UnverifiedUsing double to accelerate 32-bit integer division is relatively safe, whereas 64-bit integer division (maximum value approximately 9.2×10^18) exceeds the range that double can represent exactly and requires caution.76% similarUnverifiedPython的浮点数遵循IEEE 754双精度浮点数标准，使用64位二进制来表示一个小数72% similarUnverifiedFor double-precision floating-point numbers, one ULP near the value 1.0 is approximately 2^-52 ≈ 2.22×10^-16.69% similarUnverified32位有符号整数最大值为2,147,483,64768% similarUnverifiedSingle-precision floating-point (float, 32-bit) has only 23 mantissa bits, and can precisely represent integers in the range of approximately ±2^24.67% similar
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