64-bit proving for Jolt, without a slowdown

Jolt now proves RISC-V programs using 64-bit registers (RV64IMAC), rather than just 32-bit ones (RV32IM). And it does so at speeds exceeding those we reported two months ago for 32-bit programs:

• Over 500,000 cycles/sec on a MacBook
• Over 1,500,000 cycles/sec on a 32-core CPU

Support for 64-bit registers is important for two reasons:

• Performance: Many applications can be executed with far fewer cycles using 64-bit registers. For example, a 256-bit multiplication requires 6× fewer cycles with 64-bit registers.
• Language support: Some high-level programming languages like Go don’t currently compile to RV32IM. So if you want to prove execution of something like Geth, you need RISC-V with 64-bit registers.

So how did Jolt hit RV64IMAC speeds (cycles/sec), exceeding our RV32IM results from two months ago? 

Two reasons:

1. Jolt is built for large register sizes. Thanks to our use of large-characteristic fields, Jolt handles 64-bit values much more efficiently than other zkVMs. Most others split 32- or 64-bit values into bytes, assigning a separate field element to each. That means every 64-bit value costs 8 field elements, which must be committed and proved well-formed — a huge source of overhead.
   While other zkVMs are typically 2× slower per cycle when doubling register size, Jolt is only 1.5× slower.
2. We keep optimizing. Alongside known techniques, we’ve been adding new, research-level advances — and these gains already more than offset the 1.5× slowdown.

Memory usage is falling fast, already down to about 700 MB per million cycles (about 3× better than two months ago). That means today, in under 2 GB of space, you can prove knowledge of typical digital signatures (≈300k RV64IMAC cycles), or that dozens of KB of data were correctly SHA-hashed. 

With Twist and Shout now integrated, we’re advancing steadily. Next up: recursion, the streaming prover (keeping prover space under 2 GB for arbitrarily large cycle counts, without recursion), and zero-knowledge. As these land, Jolt’s advantages will come into even sharper focus.

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Markos Georghiades is an engineering intern at a16z crypto, where he focuses on cryptography and core Jolt development. He’s an undergraduate at the University of Waterloo studying Computer Science and Mathematics.

Andrew Milson is a Software Engineer at a16z working on the Jolt prover. Prior to this, Andrew worked at Google and at StarkWare, where his work focused on building provers and optimizing performance.

Justin Thaler is Research Partner at a16z and an Associate Professor in the Department of Computer Science at Georgetown University. His research interests include verifiable computing, complexity theory, and algorithms for massive data sets.

Andrew Tretyakov is a Cryptography Engineer at a16z crypto. He is a core contributor to the Jolt zkVM project, working on prover components, protocol architecture, and guest program optimizations.

Julius Zhang is an engineering intern at a16z crypto, where he works on Jolt. Previously, he studied Mathematics and Computer Science at Stanford.

Michael Zhu is a research engineer for a16z crypto, writing open-source code in collaboration with the research team and helping portfolio companies on all things smart contract-related. Prior to joining a16z crypto, Michael led protocol development at 0x Labs, architecting smart contracts to facilitate peer-to-peer trading on multiple blockchains. Before that, he was a student at Stanford University, where he received BS and MS degrees in Computer Science.

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