pqax aims to make it easier to start optimizing post-quantum crypto using ARM NEON. Currently, it is only tested on the Raspberry Pi 2 (which has an ARM Cortex-A7) and Raspberry Pi 4 (ARM Cortex-A72). I might add support for more hardware later.

pqax is based on mupq and works in the same manner as pqm4, except that we do not need to cross-compile and we don't need serial communication as we can just print to stdout. You can also just use supercop which should give you similar functionality.

Installation

You will need python3, make, and gcc installed.

Enable access to performance counters

To run the benchmarking you will need to enable access to the performance counters from user mode. You'll need to load a kernel module for that. You can either write one yourself, use someone else's code, or simply use the one shipped in here by

cd enable_ccr
make install

For the Raspberry Pi 2, I had to install the kernel headers manually

sudo apt install raspberrypi-kernel-headers

Testing & Benchmarking

pqax comes with most functionality supported by pqm4. Please refer to that documentation. I expect that the most common use-case of pqax is to benchmark a new NEON implementation and to test its compatibility with reference implementations. To do so, you want to place your implementation in crypto_kem/<SCHEME_NAME>/<IMPLEMENTATION_NAME> and then run the following scripts.

Testing

To test if a key encapsulation mechanism is producing the same keys for both parties, you can use the test.py script. Similarly, for signature schemes, it will test that signatures for random messages will correctly verify.

You can use it for either all schemes contained in pqax or for just a subset of schemes:

./test.py 

# or 

./test.py kyber768

Testvectors

The provided testvectors script will run the scheme with a deterministic randombytes and make sure that the output matches the one produced by reference implementations coming from PQClean and mupq.

You can use it for either all schemes contained in pqax or for just a subset of schemes:

./testvectors.py 

# or 

./testvectors.py kyber768

Note: pqm4 would run the reference implementation on the host computer and then make sure that all implementations produce the same testvectors when running bare-metal on the Cortex-M4 board. This does not make sense in the case of Cortex-A, as we are not running bare metal. However, as of now, it is still implemented like that, it's just that host and board are the same device.

Benchmarks

To benchmark the schemes, you can use the benchmarks.py script. It will run a given number of iterations. You can use it for either all schemes contained in pqax or for just a subset of schemes:

./benchmarks.py --iterations 1000

# or 

./benchmarks.py --iterations 1000 kyber768

You can then convert the output to markdown or csv using

./convert_benchmarks.py md 

# or 

./convert_benchmarks.py md 

Note: pqm4 would usually output cycle count averages (and min and max) as there is no noise when running bare-metal. On the Cortex-A, we are competing with the operating system and other processes, so there will be some noise in the cycle counts we get. Hence, we report median cycle counts.