Arithmetic Circuit Serialization for Lossless Compression
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Solution Overview
Problem
Existing blockchain technologies face challenges in efficiently storing and executing arithmetic circuits due to high data footprints, which limits their versatility beyond cryptocurrency applications and increases computational and storage requirements.
Innovation Solution
A method for lossless compression and serialization of arithmetic circuits using entropy coding and simplification rules, allowing for efficient storage and transmission by reducing redundant data fields and applying Huffman coding to frequently occurring symbols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If arithmetic circuits are stored in traditional formats, then complete information is preserved, but data footprint becomes excessively large
Solution Approach 1:
The patent applies entropy coding techniques that transform the representation parameters of arithmetic circuits from fixed-width binary formats to variable-length coded formats. By changing the parameter representation (using Huffman codes, arithmetic codes, or LZW algorithms), the circuit information is encoded more efficiently, reducing the data footprint while preserving complete reconstructability of the original circuit.
Solution Approach 2:
The patent creates compressed copies of arithmetic circuit data structures through serialization processes. Instead of storing the full uncompressed circuit representation, the system stores a compressed serialized form that can be losslessly decoded back to the original circuit, effectively using a smaller copy that contains all necessary information.
2Quantity of substance
If compression techniques are applied to arithmetic circuits, then data storage efficiency improves, but decompression complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing encoding tables, frequency distributions, and compression parameters during the circuit serialization phase. This preliminary preparation reduces the computational burden during decompression, as the decoder can use pre-computed lookup tables and algorithms rather than performing complex calculations in real-time.
Solution Approach 2:
The patent replaces complex mechanical/computational decompression operations with simpler table-driven decoding mechanisms. By substituting algorithmic complexity with pre-computed data structures (such as Huffman trees stored in tables), the system reduces the actual decompression computational load while maintaining compression efficiency.
3Measurement precision
If detailed circuit data is transmitted across the network, then execution accuracy is maintained, but network bandwidth consumption increases
Solution Approach 1:
The patent transforms the transmission parameters of circuit data by serializing and compressing the circuit representation before network transmission. By changing from transmitting raw uncompressed data structures to transmitting compressed serialized forms with associated metadata, the system maintains execution accuracy (through lossless compression) while significantly reducing network bandwidth consumption.
Data Source
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.