0xADE1A1DE / CryptOpt

CryptOpt: Verified Compilation with Randomized Program Search for Cryptographic Primitives

CryptOpt: Verified Compilation with Random Program Search for Cryptographic Primitives

CryptOpt is the result of a research project aiming to enhance the state-of-the-art of how we generate fast code for cryptographic primitives. CryptOpt is an optimizer, which feeds itself from Fiat Cryptography, generates optimized x86-64 Assembly for field arithmetic, and then feeds that Assembly back into Fiat Cryptography for end-to-end formal verification. With doing that, CryptOpt achieves much higher performance than GCC and Clang on many different micro-architectures, and in some cases even surpassing the performance hand-optimized Assembly.

The generated fast and verified assembly files are in the fiat-amd64-directory in the Fiat project and here. Here is the table from the research paper showcasing average speedups against GCC 12 / Clang 15 with respective highest optimization settings.

Geometric means of Speedup CryptOpt vs. off- the-shelf compilers.

Primitive	Mul (Clang)	Mul (GCC)	Square (Clang)	Square (GCC)
Curve25519	1.25	1.16	1.18	1.17
P-224	1.54	2.52	1.40	2.56
P-256	1.70	2.61	1.63	2.59
P-384	1.45	2.49	1.37	2.51
SIKEp434	1.70	2.43	1.73	2.39
Curve448	1.19	0.98	1.07	1.05
P-521	1.30	0.97	1.35	1.03
Poly1305	1.12	1.22	1.11	1.26
secp256k1	1.80	2.62	1.71	2.54

Use CryptOpt

If you want to optimize on your own machine, or a different primitive you can

1. Follow the instructions in the INSTALL document.
2. Run ./CryptOpt --help to check if the installation worked.
3. Run ./CryptOpt to see an optimization in action.
4. Follow the instructions in the First Steps document to get a feeling of what is going on.

The CryptOpt optimizer can also be used with non-Fiat Cryptography input. For more information see the ./test/manual-bridge/

Research Papers

The paper has been published in PLDI 2023, and is available online here and here, the BibTeX here. The full version of the paper, featuring the appendix with detailed performance measurements, is available online on arXiv here and here.

The ICSE'23 DEMO paper titled CryptOpt: Automatic Optimization of Straightline Code, which explains the technical engineering effort in more detail is available online here and here, the BibTeX here.

Tracking usage of CryptOpt

We have used CryptOpt to generate code for:

1. libsecp256k1-compatible code (./CryptOpt --curve secp256k1_dettman --memoryConstraints out1-arg1) (PR #1329)
2. BLS12-381 Curves (./CryptOpt --curve bls12_381_p, ./CryptOpt --curve bls12_381_q)
3. Curve25519 (solinas, i.e. saturated) code is integrated into BoringSSL with this commit (slight manual adaptions needed, because BoringSSL requires rbp to point to the stack. See issue #144 in this repo.)

Acknowledgements

This project was supported by:

• The Air Force Office of Scientific Research (AFOSR) under award number FA9550-20-1-0425
• the ARC Discovery Early Career Researcher Award DE200101577
• the ARC Discovery Projects DP200102364 and DP210102670
• The Blavatnik ICRC at Tel-Aviv University
• Data61, CSIRO
• the National Science Foundation under grants CNS-1954712 and CNS-2130671
• the National Science Foundation Expedition on the Science of Deep Specification (award CCF-1521584)
• the Phoenix HPC service at the University of Adelaide
• and gifts from Amazon Web Services, AMD, Facebook, Google, Intel and the Tezos Foundation.