Can the ZK real-time proof mentioned by Vitalik be achieved with ZK hardware acceleration?

Original | Odaily Planet Daily

Author | How to be a husband

During the 2024 Hong Kong Web3 Carnival, Ethereum co-founder Vitalik Buterin delivered a speech titled "Reaching the Limits of Protocol Design". In this speech, Vitalik elaborated on how to improve the efficiency of zk-snark.

In his speech, Vitalik pointed out that the current development of blockchain is based on sacrificing privacy and scalability. The properties of zk-snark can remedy the sacrificed privacy and scalability. However, zk-snark is currently inefficient. In Ethereum, it takes about 400 milliseconds for an Ethereum node to verify a block, while zk-snark takes about 20 minutes to verify an Ethereum block. This results in the network having privacy and scalability, but the running time is extended by 3,000 times. Therefore, if you want to run zk-snark in the existing blockchain network, you need to provide a "real-time proof". If the proof generation time is reduced, then while ensuring the speed of blockchain operation, it can also improve privacy and scalability.

What method can achieve "real-time proof"? For this purpose, Odaily Planet Daily will analyze the ideas provided by Vitalik in his speech and briefly introduce the projects of the corresponding solutions.

Three directions for zk-snark to achieve “real-time proof”

Before that, let’s first have a brief introduction to zk-snark. The full name of zk-snark is concise non-interactive zero-knowledge proof. For a better understanding, we explain it separately:

• Zero-knowledge proof: The prover can convince the verifier that a statement is correct without providing any useful information to the verifier.
• Simple: It means that the transaction verification process does not involve a large amount of data transmission and the verification algorithm is simple.
• Non-interactive: No interaction is required between the prover and the verifier.

The following is a flowchart of zk-snark operation. A simple interpretation of zk-snark is given in the figure:

1. Use Setup to generate the confidence parameter F using random numbers, and generate the proof key pk and verification key v
2. The prover inputs the private input W and the public input x, generates the proof π, and signs it with the private key pk. π is encrypted through the elliptic curve to hide W
3. Verifier verifies proof: The verifier holds v, inputs x and π, and confirms that the prover knows W. The verifier cannot know W
4. Result return: If the verification is successful, it returns TRUE; otherwise it returns FALSE.

Through the above introduction to the zk-snark-related process of Zcash, it is not difficult to find that zk-snark generates few steps when verifying the proof. At the same time, according to the characteristics of zk-snark, the verification time is not much. According to the corresponding zk-snark-related statistics, the verification time generally does not exceed 80 milliseconds. Therefore, the reason why zk-snark becomes an obstacle to the operation of the public chain lies in the proof provided by the prover.

The above figure is a summary of the current mainstream zk-snark related technologies. It is not difficult to find that the size of the proof, the time to generate the proof, and the verification time are the standards for measuring the relevant zk-snark technologies. Putting aside the verification time, most zk-snark proofs do not meet the standards Vitalik used Ethereum as an example at the beginning of this article in terms of proof size and generation time. It is worth noting that the public chains where most of the above technologies are located do not have the function of smart contracts, and cannot be compared with the Ethereum block size. The required proof size and proof generation time are higher.

To this end, Vitalik provided three solutions and optimization directions for the implementation of zk-snark "real-time proof" in this speech.

• Parallelization and aggregation: Improve the efficiency of verifying large blocks through parallel computing and proof aggregation. Each computational step can be independently proved, and then these proofs are aggregated to reduce the computing time and resource consumption during the verification process. This can be achieved by leveraging the characteristics of parallel computing and distributed systems to speed up the verification process of large-scale blocks.
• Hardware design improvements: Design ASICs specifically for SNARK calculations to improve computing efficiency. Similar to the ASICs used in mining, SNARK ASICs can accelerate the SNARK calculation process through customized hardware structures and optimized algorithms, thereby achieving faster verification speeds and lower costs.
• Algorithm improvement: Further optimize the snark algorithm, including Groth 16, lookup table, 64-bit snark, 32-bit stark, etc., to improve the efficiency and scalability of the algorithm. In addition, more efficient hash functions and signature algorithms can be studied and developed to make them more suitable for snark calculations, further improving verification speed and resource utilization.

Vitalik advocates the first solution direction - parallel computing and proof aggregation, which requires optimization of the relevant public chain and zk-snark operation process, such as the recursive property of the Plonk algorithm in the previous zk-snark algorithm. However, there is currently no better solution to parallel computing and proof aggregation to solve the corresponding problems.

As for algorithm improvement, currently in the field of zk-snark, from the performance point of view, the mainstream is still the Groth 16 algorithm. The subsequent zk-snark algorithms are mostly to solve the problem of trusted settings, and there is no further progress in running speed and proof generation time. In addition, in the zk-snark algorithm, the trusted settings are relatively simple, the faster the running speed, but the worse the security. Therefore, with security as the premise, the speed of zk-snark improvement needs to be continuously developed.

The above two solutions are mainly based on theory, which takes a long time to achieve a breakthrough. So, apart from theory, can we quickly achieve "real-time proof" through other means? Hardware design improvement may be the best shortcut to achieve the goal.

ZK hardware acceleration may enable “real-time proof” as soon as possible

From the previous content about zk-snark performance, it is not difficult to find that the real limitation of zk-snark performance lies in the generation of proofs, where the proof size and circuit scale determine the proof generation time. At present, the complexity of most projects is getting higher and higher, and their proof size and circuit scale are also constantly increasing, and the computing power of generating proofs is also increasing. For this reason, the ZK hardware acceleration project came into being.

ZK hardware acceleration mainly provides computing power support for polynomial type NTT tasks and elliptic curve MSM tasks in proof generation. The operating logic of these two tasks is simple, most of the calculation logic is repeated, and parallel calculations can be performed.

ZK hardware is not much different from mining hardware, and there are still three types of GPU, FPGA and ASIC. However, the GPU/FPGA solution is more common in the field of ZK hardware acceleration. This solution is easier to implement and related accessories are easier to obtain. However, compared with the former two, ASIC has greater potential and is also one of the current growth points in the field of ZK hardware acceleration.

Currently, the ZK hardware acceleration project provides computing power services for related ZK projects in two ways, including hardware sales and SaaS computing power services. Hardware sales, as the name implies, sell mining machines like Bitmain; SaaS computing power services are more like providing a computing power market, where ZK projects can purchase computing power to help the project generate ZK proofs.

Currently, the ZK hardware acceleration field is relatively niche. If Vitalik hadn't mentioned it in his speech, most people would not know what projects exist. For this reason, Odaily Planet Daily sorted out the projects in this section. There are relatively few projects in this section, among which Cysic, Ingopedia, Supranational, Ulvantanna and Auradine are currently more well-known projects.

Among them, Cysic currently has the highest attention. Its FPGA/ASIC hardware acceleration is more prominent in computing power performance, and it also has a computing power market to provide computing power support services for customers; Auradine is more comprehensive. It mainly promotes Bitcoin mining machines and provides corresponding ZK computing power hardware, but ZK hardware is not its main product; Ulvantanna mainly uses FPGA clusters to provide computing power support for ZK projects. It is worth mentioning that Paradigm, a well-known Web3 capital, is its investor; Supranational project is rather peculiar. The updates on Twitter and the official website ended in May last year, and it is uncertain whether it is currently running; Ingopedia provides two hardware acceleration services based on GPU and FPGA.