Arithmetic Circuit Serialization for Lossless Data Footprint Reduction

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Solution Overview

Problem

Current technologies face challenges in efficiently reducing the data footprint of arithmetic circuits, which is crucial for storage in disk or memory, especially in distributed computing environments like blockchain networks.

Innovation Solution

The method involves removing redundant data fields from arithmetic circuits and applying entropy coding schemes to compress the remaining data, resulting in a serialized circuit that can be stored efficiently and later de-serialized losslessly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If arithmetic circuits are stored in their original format, then complete information is preserved, but data footprint is large and storage efficiency is low

Engineering Contradiction:
Improvedata footprintVSAvoidinformation completeness
Core Design Contradiction:
Quantity of substanceVSLoss of information

Solution Approach 1:

The patent extracts and removes redundant data fields from arithmetic circuits before storage. Specifically, it identifies and eliminates fields that can be derived from other fields (e.g., removing wire identifier fields when cardinality information is available), thereby reducing data footprint while preserving the ability to reconstruct complete circuit information.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent applies entropy coding schemes to transform the representation of arithmetic circuit data. By changing the parameter representation from raw field values to compressed encoded forms, the data footprint is significantly reduced while maintaining lossless reconstructability of the original circuit information.

Inventive Principle:
Principle #35Parameter changes

2Quantity of substance

If compression techniques are applied to reduce data footprint, then storage efficiency improves, but circuit reconstruction complexity increases

Engineering Contradiction:
Improvestorage efficiencyVSAvoidcircuit reconstruction complexity
Core Design Contradiction:
Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent performs preliminary organization and structuring of arithmetic circuit data before compression. By pre-identifying redundant fields and establishing a systematic removal approach, the reconstruction process becomes more straightforward despite the compression applied, as the structure of the compressed data reflects the original circuit hierarchy.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary compression layer that uses entropy coding with embedded de-serialization instructions. This intermediary structure acts as a bridge between the compressed form and the original circuit representation, providing guidance for reconstruction and reducing the complexity of recovering the original circuit from compressed data.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Quantity of substance

If redundant data fields are removed, then data footprint is reduced, but data retrieval difficulty increases

Engineering Contradiction:
Improvedata footprintVSAvoiddata retrieval difficulty
Core Design Contradiction:
Quantity of substanceVSDifficulty of detecting and measuring

Solution Approach 1:

The patent embeds de-serialization instructions within the compressed data structure that provide feedback during the reconstruction process. These instructions guide the systematic recovery of removed fields from the remaining data and compression metadata, making the retrieval process automated and reducing the difficulty of reconstructing the original circuit information.

Inventive Principle:
Principle #23Feedback

4Quantity of substance

If entropy coding is applied to compress arithmetic circuits, then storage requirements decrease, but processing time increases

Engineering Contradiction:
Improvestorage requirementsVSAvoidprocessing time
Core Design Contradiction:
Quantity of substanceVSLoss of time

Solution Approach 1:

The patent applies entropy coding selectively to specific portions of the arithmetic circuit data that exhibit higher redundancy, rather than uniformly compressing all fields. By focusing compression efforts on the most redundant elements (such as repeated wire identifiers or patterned field sequences), the patent achieves significant storage reduction while minimizing the processing overhead associated with compression and decompression operations.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP4224716B1Computer-implemented systems and methods for serialisation of arithmetic circuits
Publication Date: 2025.01.29 NCHAIN LICENSING AG
  • EP4224716B1 patent drawingFigure 1
  • EP4224716B1 patent drawingFigure 2
  • EP4224716B1 patent drawingFigure 3

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.