TensorFloat-32
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| Floating-point formats |
|---|
| IEEE 754 |
|
| Other |
| Alternatives |
| Tapered floating point |
TensorFloat-32 (TF32) is a numeric floating point format designed for Tensor Core running on certain Nvidia GPUs. It combines the 8-bit exponent size of IEEE single precision with the 10-bit mantissa size of half precision.
Format
[edit | edit source]The binary format is:
- 1 sign bit
- 8 exponent bits
- 10 significand bits (also called mantissa, or precision bits)
File:General floating point.svg
The 19-significant-bit format fits within a double word (32 bits), and while it lacks precision compared with a normal 32-bit IEEE 754 floating-point number, provides much faster computation, up to 8 times on a A100 (compared to a V100 using FP32).[1]
Stored in the same space as FP32, it is not really a distinct storage format, but a specification for reduced-precision FP32 multiply–accumulate operations. FP32 inputs are rounded to TF32, multiplied to produce a 21-bit product (including the implcit msbit, this is an 11×11→22-bit multiply), and summed into a standard FP32 accumulator.[2]
See also
[edit | edit source]References
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