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update readme to include float32 support #10

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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -77,7 +77,7 @@ The rANS codec operates on 8 bit bytes. It can compress arbitrary data, but usin

## Float codec

The floating point compressor at the moment uses the rANS codec to handle compression of floating point exponents, as typically in ML/HPC data a very limited exponent dynamic range is used and is highly compressible. Floating point sign and significand values tend to be less compressible / fairly high entropy in practice, though sparse data or presence of functions like ReLU in neural networks can result in a lot of outright zero values which are very compressible. A future extension to the library will allow for specialized compression of sparse or semi-sparse data, specializing compression of zeros. At the moment only float16 (IEEE 754 binary16) and bfloat16 (fields of the most significant 16 bits of a IEEE 754 binary32 word) are supported, with float32 (IEEE 754 binary32) support coming shortly.
The floating point compressor at the moment uses the rANS codec to handle compression of floating point exponents, as typically in ML/HPC data a very limited exponent dynamic range is used and is highly compressible. Floating point sign and significand values tend to be less compressible / fairly high entropy in practice, though sparse data or presence of functions like ReLU in neural networks can result in a lot of outright zero values which are very compressible. A future extension to the library will allow for specialized compression of sparse or semi-sparse data, specializing compression of zeros. At the moment only float16 (IEEE 754 binary16), float32 (IEEE 754 binary32), and bfloat16 (fields of the most significant 16 bits of a IEEE 754 binary32 word) are supported, with float64 (IEEE 754 binary64) support coming later.

## API design

Expand All @@ -98,7 +98,7 @@ Performance depends upon many factors, including entropy of the input data (high

## Planned extensions

- float32 support, possibly float64 support
- float64 support
- compression options to expect semi-sparse floating point data for higher compression (>10% zero values)
- a fused kernel implementation (likely using CUDA cooperative groups) to support single-kernel compression and decompression minimizing temporary memory usage
- a fused kernel implementation using the above to support persistent NCCL-like all-reduce for collective communications libraries
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