TRCE — Thermodynamic Reservoir Computing Engine

核心理念

传统 ML: 软件在 GPU 上算矩阵乘法
TRCE: 硅片的热传导完成非线性变换,软件只做 I/O + 线性 Readout

硬件拓扑

项目结构

TRCE/
├── Cargo.toml # Workspace 根
├── pyproject.toml # maturin 构建配置
├── crates/
│ ├── trce-core/ # Rust 核心库
│ │ └── src/
│ │ ├── lib.rs
│ │ ├── engine.rs # Typestate 引擎 (Uninitialized → Calibrated → Running → Released)
│ │ ├── hardware/ # sysfs I/O 层
│ │ │ ├── thermal_zone.rs
│ │ │ ├── cooling_device.rs
│ │ │ ├── cpu_affinity.rs
│ │ │ ├── governor.rs
│ │ │ └── thermald.rs
│ │ ├── inference/ # 推理管线
│ │ │ ├── pulse.rs # 热脉冲注入 (black_box 防优化)
│ │ │ ├── readout.rs # 线性分类器 (8-dim 点积 + sign)
│ │ │ ├── signal.rs # 梯度、基线扣除、指数移动平均
│ │ │ └── stream.rs # tokio MPSC 流式推理
│ │ ├── training/ # 离线训练
│ │ │ ├── fit.rs # OLS / Ridge 回归 (手写 Gaussian elimination)
│ │ │ └── fingerprint.rs # 多窗口物理指纹采集
│ │ ├── telemetry/ # 遥测
│ │ │ ├── metrics.rs
│ │ │ └── watchdog.rs # 独立 OS 线程超温熔断
│ │ ├── serialization/
│ │ │ └── weights.rs # 权重序列化 (原生字节格式)
│ │ └── privilege/
│ │ └── mod.rs # root 检测、提权策略
│ └── trce-py/ # PyO3 Python 绑定
│ └── src/lib.rs
├── python/trce/ # Python 封装层
│ ├── __init__.py
│ ├── engine.py # ThermodynamicEngine Python 接口
│ ├── training.py # DesignMatrix, ReadoutWeights, fit_readout
│ └── daemon.py # 守护进程入口 (自动提权)
├── deploy/
│ └── trce.service # systemd 服务单元
└── examples/
 └── basic_inference.py

快速开始

环境要求

构建

# 克隆仓库
git clone <repo-url> && cd TRCE
# 创建 Python 虚拟环境
python3 -m venv .venv && source .venv/bin/activate
# 安装 maturin
pip install maturin numpy
# 构建并安装 PyO3 扩展
maturin develop --release

基本推理

from trce import ThermodynamicEngine
with ThermodynamicEngine() as engine:
 engine.calibrate_baseline(5) # 采样 5 秒空载温度
 engine.load_weights_from_file("weights.bin")
 features = [0.5, 0.3, 0.7, 0.2]
 result = engine.inject_and_predict(features)
 print(f"Prediction: {result.prediction}, Confidence: {result.confidence:.4f}")

训练拟合

from trce.training import DesignMatrix, fit_readout
# 收集物理指纹 (需要真实硬件)
# samples: 28-dim 向量 (6 时间窗口 ×ばつ 4 热区 + 4 dT/dt)
# labels: +1 或 -1
matrix = DesignMatrix(samples, labels)
# 拟合 Readout 权重
weights = fit_readout(matrix, method="ridge", alpha=0.1)
# 保存权重
weights.save("weights.bin")

架构 (4 阶段,严格顺序)

Typestate 生命周期

Uninitialized ──init_hardware_harness()──▶ Calibrated
 │
 load_weights()
 │
 ▼
 Running ──release()──▶ Released

API 一览

Rust (trce-core)

Python (trce)

关键设计决策

部署

systemd 服务 (推荐)

sudo cp deploy/trce.service /etc/systemd/system/
sudo systemctl daemon-reload
sudo systemctl enable --now trce

手动运行

sudo .venv/bin/python -m trce.daemon

物理参数调优

热脉冲

多窗口采样

冷却策略

依赖

Rust

Python

风险与缓解

License