https://github.com/murrellgroup/microfloats.jl
Slow, low-precision floating point types
https://github.com/murrellgroup/microfloats.jl
floating-point fp4 fp6 fp8 microfloat microscaling minifloat
Last synced: 4 months ago
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Slow, low-precision floating point types
- Host: GitHub
- URL: https://github.com/murrellgroup/microfloats.jl
- Owner: MurrellGroup
- License: mit
- Created: 2025-08-07T21:10:17.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-09-01T11:34:13.000Z (9 months ago)
- Last Synced: 2025-09-01T12:36:42.068Z (9 months ago)
- Topics: floating-point, fp4, fp6, fp8, microfloat, microscaling, minifloat
- Language: Julia
- Homepage:
- Size: 295 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 
Microfloats
[](https://MurrellGroup.github.io/Microfloats.jl/stable/)
[](https://MurrellGroup.github.io/Microfloats.jl/dev/)
[](https://github.com/MurrellGroup/Microfloats.jl/actions/workflows/CI.yml?query=branch%3Amain)
[](https://codecov.io/gh/MurrellGroup/Microfloats.jl)
Microfloats is a Julia package that implements types and arithmetic (through wider intermediates) for sub-8 bit floating points, supporting arbitrary combinations of sign, exponent, and mantissa (significand) bits.
Instances of a sub-8 bit floating point type are still 8 bits wide in memory; the goal of `Microfloat` is to serve as a base for arithmetic operations and method dispatch, lending downstream packages a good abstraction for doing bitpacking and hardware acceleration.
## Usage
Along with the types already exported by Microfloats, we can also create our own types by passing the number of sign, exponent, and mantissa bits to the `Microfloat` type constructor. For example, one can recreate the `Float8` and `Float8_4` types exported by Float8s.jl:
```julia
using Microfloats
# IEEE_754_like variant for {Float64,Float32,Float16}-like overflowing
const MicrofloatIEEE{S,E,M} = Microfloat{S,E,M,IEEE_754_like}
const Float8 = MicrofloatIEEE{1,3,4}
const Float8_4 = MicrofloatIEEE{1,4,3}
# creating a sawed-off Float16 (BFloat8?) becomes trivial:
const Float8_5 = MicrofloatIEEE{1,5,2}
# unsigned variants:
const UFloat7 = MicrofloatIEEE{0,3,4}
const UFloat7_4 = MicrofloatIEEE{0,4,3}
const UFloat7_5 = MicrofloatIEEE{0,5,2}
```
### Microscaling (MX)
Microfloats implements the E4M3, E5M2, E2M3, E3M2, E2M1, and E8M0 types from the [Open Compute Project Microscaling Formats (MX) Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf). These are exported as `MX_E4M3`, `MX_E5M2`, `MX_E2M3`, `MX_E3M2`, `MX_E2M1`, and `MX_E8M0`, respectively, with most of these using saturated arithmetic (no Inf or NaN), and a different encoding for the types that do have NaNs.
For INT8, see `FixedPointNumbers.Q1f6`.
> [!NOTE]
> MX types may not be fully MX compliant, but efforts have been and continue to be made to adhere to the specification. See issues with the [](https://github.com/MurrellGroup/Microfloats.jl/labels/mx-compliance) label.
Since Microfloats.jl only implements the primitive types, microscaling itself may be done with [Microscaling.jl](https://github.com/MurrellGroup/Microscaling.jl), which includes quantization and bitpacking.
## Installation
```julia
using Pkg
Pkg.Registry.add(url="https://github.com/MurrellGroup/MurrellGroupRegistry")
Pkg.add("Microfloats")
```
## See also
- [Microscaling.jl](https://github.com/MurrellGroup/Microscaling.jl)
- [FixedPointNumbers.jl](https://github.com/JuliaMath/FixedPointNumbers.jl)
- [MicroFloatingPoints.jl](https://github.com/goualard-f/MicroFloatingPoints.jl)
- [DLFP8Types.jl](https://github.com/chengchingwen/DLFP8Types.jl)
- [Float8s.jl](https://github.com/JuliaMath/Float8s.jl)