EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Lobsters·Jul 24·5 min read
ALP: Adaptive Lossless Floating-Point Compression
TL;DR
ALP is a novel lossless compression algorithm for IEEE 754 floating-point data, achieving efficient encoding by leveraging common patterns in real-world datasets. It significantly reduces storage requirements while preserving precision, making it ideal for high-precision applications.
✦ Why It Matters
Implement ALP in your data processing pipeline to optimize storage and enhance performance for floating-point datasets.
Key Takeaways
- Use ALP for efficient floating-point data compression.
- Leverage FastLanes for SIMD-friendly encoding.
- Benchmark your datasets with provided scripts.
- Join the ALP community for updates and support.
How It Works
ALP compresses decimal floating-point numbers by converting them into integers through multiplication by a power of 10, then applying FastLanes encoding. For high-precision floats, it compresses only the left part using FastLanes dictionary encoding, leaving the right part uncompressed to maintain precision.