Arithmetic Circuit Serialization Using Redundant Field Extraction
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Solution Overview
Problem
Current technologies face challenges in efficiently reducing the data footprint of arithmetic circuits, particularly in distributed computing environments like blockchain networks, where storage and transmission of circuits are resource-intensive.
Innovation Solution
The method involves removing redundant data fields and applying entropy coding to arithmetic circuits, generating a serialized circuit that can be losslessly decompressed, thereby reducing the data storage and transmission requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If arithmetic circuits are stored in full form, then data integrity and completeness are maintained, but storage space and transmission bandwidth are excessively consumed
Solution Approach 1:
The patent extracts only the essential components needed for circuit reconstruction. By identifying and removing redundant data fields (those obtainable from other fields), the system keeps only the minimal necessary data subset, achieving both compression and data integrity.
Solution Approach 2:
The patent applies entropy coding schemes (such as Huffman coding) in advance to encode the essential data fields before storage or transmission. This preliminary compression action reduces the data footprint while maintaining the ability to perfectly reconstruct the original circuit through lossless decompression.
2Quantity of substance
If arithmetic circuits are compressed using entropy coding, then data footprint is reduced, but computational overhead for encoding and decoding increases
Solution Approach 1:
The patent applies partial compression by selectively encoding only the essential data fields rather than the entire circuit representation. This partial action approach reduces the overall computational overhead while still achieving significant data footprint reduction through targeted entropy coding on the most important components.
3Quantity of substance
If redundant data fields are removed, then storage efficiency improves, but circuit reconstruction complexity increases
Solution Approach 1:
The patent incorporates feedback mechanisms in the reconstruction process. The decompression system uses the encoded essential fields to reconstruct the removed redundant fields through deterministic relationships, ensuring that the reconstruction process, while slightly more complex, remains systematic and reliable through feedback-based verification.
Data Source
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AI summary
Techniques described herein may be utilized to serialise and de-serialise arithmetic circuits that are utilized in the execution of computer programs. The arithmetic circuit may be utilized to build a Quadratic Arithmetic Problem (QAP) that is compiled into a set of cryptographic routines for a client and a prover. The client and prover may utilize a protocol to delegate execution of a program to the prover in a manner that allows the client to efficiently verify the prover correctly executed the program. The arithmetic circuit may comprise a set of symbols (e.g., arithmetic gates and values) that is compressed to produce a serialised circuit comprising a set of codes, wherein the set of symbols is derivable from the set of codes in a lossless manner. Serialisation and de-serialisation techniques may be utilized by nodes of a blockchain network.