ADR-001 CORE accepted

Middle-Out Compression Algorithm

2014-04-15
Authors: Richard Hendricks

Middle-Out Compression Algorithm

Context

Standard compression algorithms use either bottom-up (Huffman coding) or top-down (Shannon coding) approaches. Both have theoretical limits that have constrained the industry for decades.

Richard Hendricks discovered a revolutionary "Middle-Out" approach while working on a music plagiarism detection app. The compression engine underlying the app demonstrated ratios that defied established theoretical limits.

Decision

Implement bidirectional "Middle-Out" compression that starts from the statistical center of a data block and compresses outward in both directions simultaneously.

Technical Details

The Middle-Out Heuristic

Raw Data BlockStatistical CenterForward StreamBackward StreamCross-ReferenceCompressed Output Find centercenter → endcenter → startRedundanciesRedundanciesMerge with shared dictionary
flowchart TD
    A[Analyze data block] --> B[Find statistical center]
    B --> C[Create parallel streams]
    C --> D[Forward: center → end]
    C --> E[Backward: center → start]
    D --> F[Cross-reference redundancies]
    E --> F
    F --> G[Merge with shared dictionary]
    G --> H[Compressed output]

Weissman Score Achievement

The algorithm achieved a Weissman Score of 5.2 at TechCrunch Disrupt, breaking the previously believed theoretical maximum of 2.9.

$$W = \alpha \frac{r}{\bar{r}} \frac{\log(\bar{T})}{\log(T)}$$

Where:

  • r = compression ratio achieved (our algorithm)
  • r̄ = baseline compression ratio (GZIP)
  • T = time for our algorithm
  • T̄ = time for baseline
  • α = scaling constant

Performance Characteristics

Data TypeCompression RatioSpeed vs GZIP
Text8.2:11.4x faster
3D Video12.1:12.1x faster
Genomic15.3:11.8x faster

Consequences

Positive

  • +Industry-leading compression technology
  • +Competitive moat against Hooli Nucleus
  • +Foundation for all future products (Platform, Box, PiperNet)

Negative

  • High complexity makes maintenance difficult
  • Single point of failure if algorithm is compromised
  • Triggered Hooli IP lawsuit (see INC-001)

Implementation Notes

The algorithm is implemented in C with SIMD optimizations for parallel processing. GPU acceleration available via CUDA kernels.

// Core middle-out entry point
int piper_compress(
    const uint8_t* input,
    size_t input_len,
    uint8_t* output,
    size_t* output_len,
    int compression_level
);
ADR-001 Authors: Richard Hendricks