Pseudorandom Correlation Generators (PCGs) have emerged as a powerful and versatile tool in the design of efficient secure computation protocols. This talk traces the development of PCGs: lightweight cryptographic primitives that allow a pair of parties to expand a short seed into a large volume of correlated randomness, without interaction and with strong security guarantees. I will survey key constructions of PCGs for OT correlations and Beaver triples, discuss their surprising efficiency, and highlight how they outperform traditional approaches by several orders of magnitude in both computation and communication.

Finally, we reflect on how the success of PCGs reshapes the cryptographic landscape—suggesting new protocol paradigms, improving precomputation pipelines, and paving the way for highly scalable secure computation.

Modular arithmetic is the computational backbone of many cryptographic and scientific algorithms.
In particular, modular multiplication in a large prime field is computationally expensive and dictates the runtime of many algorithms. While it is relatively easy to utilize vectorization to accelerate batches of independent modular multiplications, we show how to significantly reduce the latency of a single modular multiplication under a generic prime using vectorization. We achieve this using a new RNS Montgomery multiplication method that has a simplified structure (in relation to prior art) and that we conjecture has no unnecessary elementwise modular multiplications. This means that virtually all of (number-theoretic) cryptography can be sped up using vectorization.