Elias emphasized the current limitations of Ethereum's transaction speed, stating it can only handle about 30 transactions per second. He pointed out that with the implementation of rollups, this can be pushed to around 300 transactions, but this is still insufficient compared to competitors like Solana, which can achieve 4,000 sustained transactions per second, or Visa, which can reach 60,000 transactions per second. The pivotal challenge is to scale Ethereum while maintaining its core values of verifiability and security.
2. Importance of Verifiability in Blockchain
Elias highlighted that in Ethereum's context, the focus should not solely be on speed but instead on verifiability. He suggested that implementing zero-knowledge (ZK) proofs allows for the separation of heavy computation from verification processes without compromising the core value of the blockchain. This push towards efficient proof systems is critical as Ethereum prepares to evolve and respond to community demands for better performance.
3. Developing Real-time Proving Systems
Elias introduced the concept of real-time proving, explaining that ZK rollups currently generate proofs outside the real-time constraints of block creation, sometimes taking hours. He pointed out that the next frontier for ZK technology is to generate these proofs much faster—ideally under the 12-second window allowed for block creation. Achieving this will require significant improvements in proof generation time and creative engineering solutions.
4. Bottlenecks in ZK Proof Generation
During his talk, Elias outlined critical bottlenecks in the ZK proving process, such as the data pre-processing time, which can take a significant amount of time due to latency when querying blockchain state data. He noted that in an optimal scenario, this step could ideally take no longer than 1 second. He acknowledged that current methodologies are behind schedule and that optimized coding practices are required to mitigate this.
5. Parallelization of Tracing
Elias mentioned the potential solution of parallelizing tracing to overcome current speed limitations in proof generation and verification. Through parallel execution, he believes teams can significantly reduce the time it takes to validate each state during the proofing process. This innovative approach aligns with engineering best practices that seek to enhance performance by maximizing resource utilization.
6. Hardware Accelerations and Cost Implications
Elias discussed how hardware accelerations, including GPU optimizations, could play a pivotal role in speeding up proof generation while making the process cost-efficient. He explained that assembling numerous GPUs could accelerate processes, but this requires balancing between speed and expense. As teams work to design and implement optimized libraries for these technologies, costs should remain manageable.
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