Polyhedra Sets Sights on Ethereum Roadmap & ZKML after Unlocking Massive ZK Performance Gains via GPU Acceleration

Polyhedra, the team behind the world’s fastest prover, Expander, and the leading zero-knowledge interoperability protocol, zkBridge, announced that they have achieved an over 2000X performance improvement for certain zero-knowledge proof systems via GPU acceleration. 

The recent research from the Polyhedra team focused on harnessing the processing capabilities of GPUs to optimize key components of the Sumcheck protocol, which their proof system Expander utilizes. 

Results (GPU vs. Single-thread CPU)

*OOM means out of memory; CPU is single-thread implementation running on Intel(R) Xeon(R) Platinum 8460Y+

These results could have a far-reaching impact on applications of the cryptographic primitive often used for its scalable, secure, and verifiable characteristics. 

“ZK has evolved. What began as a privacy-focused technology is now a gateway to blockchain scalability,” says Tiancheng. “Expander is the culmination of years of research and a solution to the computational limitations that held ZK back. Today, we’ve not only made ZK faster and more cost-effective but have unlocked its potential for mass adoption in real-world decentralized applications, from traditional finance to AI.”

ZKML

The exponential growth in the utilization of artificial intelligence (AI) has led to concerns about AI safety and privacy. AI systems are increasingly being used for critical decision-making across industries like healthcare, finance, and transportation. This has raised concerns about the potential for AI systems to be biased or inaccurate, and for user data to be misused or compromised.

Zero-knowledge proofs (ZKPs) offer a promising solution to these concerns. ZKPs are a cryptographic technique that allows one party (the prover) to prove to another party (the verifier) that they know a certain piece of information (the secret) without revealing the secret itself. This makes it possible to create AI systems that are transparent and verifiable, without compromising the privacy of user data.

zkML is a specific type of ZKP designed for use with machine learning models. zkML allows users to prove that a model has been trained correctly and that it is making accurate predictions, without revealing the underlying data that was used to train the model. This can help to address concerns about AI bias and inaccuracy.

zkML can also be used to protect user privacy. When users interact with AI systems, they often provide personal data, such as their medical records or financial information. This data can be sensitive and could be misused if it is compromised. zkML can ensure that an AI system processes users' data securely and generates correct outputs, all while keeping the data private. 

One of the main challenges with ZKPs has been performance. Generating and verifying ZKPs can be computationally expensive, which has limited their practical applications. Fortunately, recent advances by the Polyhedra team have significantly improved the performance of ZKPs. This makes it possible to use ZKPs in real-world applications, such as AI safety and privacy.

The use of ZKPs in AI has the potential to revolutionize the way we interact with AI systems. By making AI systems more transparent, verifiable, and private, ZKPs can help to build trust in AI and open up new possibilities for its use.

Ethereum Roadmap

Recently, Vitalik penned a blog post on Ethereum’s future, specifically the Verge, which is aimed to improve scalability and decrease complexity of the Ethereum network.

“Today, the Verge represents a much larger vision focused on enabling maximally resource-efficient verification of the Ethereum chain, which includes not just stateless validation technology, but also verifying all Ethereum execution with SNARKs,” Vitalik wrote regarding the Verge. 

The primary technology necessary to achieve this milestone is ZKP, but until recently it was viewed as non-viable due to technical complexity and performance bottlenecks. With recent improvements to ZKP technology and specifically Polyhedra’s advancements with GPU acceleration, these goals have moved from infeasible to achievable in just a short period of time. 

It will not be long before full nodes require negligible amounts of storage (a few GBs) and full verification of Ethereum consensus can be done on any mobile device via a zero-knowledge proof. 

Future Work

While the Polyhedra team is extremely excited about the results of their recent work they are not slowing down on the research front. Future research efforts will focus on: 

1. End-to-End Optimization: Accelerating remaining operations that may be less hardware-friendly.
2. Cross-Platform Performance: Further tuning for a wider range of GPU architectures.
3. Integration with Ethereum Clients: Collaborating with client teams to implement these optimizations.

“This is a defining moment for blockchain technology,” adds Tiancheng. “With Expander, we’re proving that ZK is ready for mass adoption, and to shape the future of innovative products.”

About Polyhedra Network
Polyhedra Network is at the forefront of blockchain innovation, specializing in zero-knowledge technology that enhances privacy, scalability, and security. With a mission to accelerate the adoption of decentralized applications, Polyhedra continues to evolve blockchain scalability for AI, machine learning interoperability, gaming, TradFi, and the future of zero-knowledge systems.

This post is commissioned by Polyhedra Network and does not serve as a testimonial or endorsement by The Block. This post is for informational purposes only and should not be relied upon as a basis for investment, tax, legal or other advice. You should conduct your own research and consult independent counsel and advisors on the matters discussed within this post. Past performance of any asset is not indicative of future results.