# Adaptive Pipeline Cache
A high-performance adaptive caching system implemented in C++ with Python bindings. The cache dynamically adjusts its internal structure based on workload characteristics, combining FIFO, Approximate LRU (ALRU), and Cost-Aware LFU strategies.
## Features
- **Adaptive Architecture**: Automatically adjusts cache structure based on workload patterns
- **Multiple Eviction Policies**: Combines FIFO, ALRU, and Cost-Aware LFU in a pipeline
- **High Performance**: Implemented in C++20 with efficient memory management
- **Python Integration**: Clean Python API via pybind11
- **Cost-Aware**: Takes into account both latency and token costs for eviction decisions
## Installation
```bash
pip install adaptive-pipeline
```
### Building from Source
Requirements:
- C++20 compatible compiler
- CMake >= 3.15
- Python >= 3.7
- pybind11 >= 2.6.0
```bash
git clone <repository-url>
cd pipeline-cache
pip install -e .
```
## Usage
Notice that for this version, the size of the cache is hard-coded to be 1024, and it ignores the size parameter.
```python
from adaptive_pipeline import AdaptivePipelineCache
# Create a cache with capacity of 1024 items
cache = AdaptivePipelineCache(1024)
# Store items with (latency, tokens) tuple
cache[key] = (latency, tokens)
# Check if key exists
if key in cache:
latency, tokens = cache[key]
# Get cache statistics
print(f"Current size: {cache.currsize}")
print(f"Max size: {cache.maxsize}")
```
## How It Works
The Adaptive Pipeline Cache uses a novel approach that:
1. **Pipeline Structure**: Divides the cache into three blocks (FIFO, ALRU, Cost-Aware LFU)
2. **Dynamic Adaptation**: Periodically evaluates alternative configurations using "ghost caches"
3. **Quantum-Based Resizing**: Moves chunks of items between blocks based on performance metrics
4. **Cost-Aware Eviction**: Considers both access frequency and cost (latency × tokens) for eviction decisions
The cache automatically adapts its configuration every 10,240 operations (configurable) by comparing the performance of the current configuration against alternative configurations simulated by ghost caches.
## Interface Compatibility
The implementation follows the interface of `cacheutils` for compatibility with GPT-Cache experiments.
## License
MIT License - see LICENSE file for details
## Author
Nadav Keren (nadavker@pm.me)
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