A brief analysis of Reddio's latest white paper: Automated AI + parallel EVM to make up for the shortcomings of Ethereum's ecosystem

After reading the latest white paper released by Reddio, it is true that automated AI execution is integrated into the EVM narrative, which is equivalent to filling the gap in the entire Ethereum ecosystem in the AI ​​track. Very Make Sense, so why can parallel EVM seamlessly connect to AI? What are the logic and technical principles behind it? Let me briefly explain the understanding:

1. The "parallel EVM" narrative has always been characterized as a key battle to smooth the gap between the iteration of high-performance chain technologies such as Solana and Sui. Therefore, the previous market's hype expectations for Sei and Monad's huge financing of US$225 million have pushed parallel EVM to an unprecedented level.

In contrast, Reddio, as a parallel EVM public chain led by Paradigm, seems to be much more low-key, and has no market expectations such as financing, ICO, and KOL rounds. It is just showing off its test network's stable TPS data. Recently, the official snapshot was announced, and it was obvious that it would take the lead to verify the niche value of parallel EVM in the Ethereum ecosystem.

2. So, why is parallel EVM an effective supplement to the technical capability bottleneck of the Ethereum ecosystem? Simply put, the original single-threaded execution + serial execution in transaction order of EVM is an inherent limitation. Parallel EVM uses the parallel computing power of modern hardware (CPU, GPU), coupled with some I/O asynchronous storage processing, state access optimization processing, etc. to achieve simultaneous execution of large-scale batch transactions.

The technical implementation logic revealed in the Reddio white paper is roughly the same. Reddio has an execution network composed of GPU nodes, and through the CUDA "encoding translator", it converts ordinary EVM opcode programs into complex and intensive computing tasks that can implement computing in the GPU. In addition, other I/O asynchronous storage optimization, state access management optimization, optimistic concurrency control, etc., realizes the ability to process transactions in parallel;

3. Since parallel EVM essentially plays the performance advantages of "hardware", AI application scenarios naturally require large-scale parallel computing and intensive computing processing. A powerful set of hardware can play a role in parallel EVM and AI application scenarios at the same time. In this way, another layer of narrative imagination space for parallel EVM + AI is opened. Parallel EVM chains can enable AI large-scale deployment and on-chain, and allow smart contracts to directly control and schedule AI, and then apply data privacy and verifiability capabilities related to ZK, TEE, etc., which can realize the native fusion of blockchain and AI. For example, AI real-time reasoning, AI Oracle, off-chain AI trading strategy optimization, etc.