VermiIIi0n/parahash

Parallel Hashlib

Collection of some hash functions implemented with torch/numpy/tensorflow

WORK IN PROGRESS!

Installation

pip install parahash

or clone this repo and run

pip install -U poetry
poetry install -E all

# To install to your current environment, do
# pip install .

Some dependencies are optional when installing because they are not required or you may need a custom-built version of torch/tensorflow/numpy. Make sure to install them if you need them.

MD5

import parahash
from bitarray import bitarray

device = "cpu"
# device = "cuda"

data = [b'hello', "world", bitarray('1101010101010101010101010101010101010101010101010101010101010101')]

for out in parahash.md5.md5(data, device=device):
    print(parahash.md5.hexdigest(out))

Current implementation with enough batch size can get 20 million single-block(<=448bits) hashes per second on a single RTX3090 GPU, 16 million hashes per second on a single RTX4070TiS GPU and 750K hashes per second on a single 7950x CPU.