Synaptic-Delta-Sync (SDS) is a high-performance, production-grade infrastructure library designed for atomic, secure, and zero-downtime neural network weight updates.
In modern AI environments, updating models often requires a full restart, leading to service disruption. SDS bridges this gap by enabling hot-swapping of weights directly into live inference engines without stopping the process.
The SDS pipeline is designed for modularity, speed, and integrity. The architecture separates weight extraction, cryptographic validation, and device-specific injection into distinct, highly optimized layers.
graph TD
subgraph "Phase 1: Preparation"
A[Live Model] -->|Extract| B[Delta Engine]
B -->|Sparse Diff| C[Serialized .sds Patch]
end
subgraph "Phase 2: Injection"
C -->|Verify| D[Patch Validator]
D -->|Hash Check| E[Atomic Injector]
end
subgraph "Phase 3: Execution"
E -->|Route| F{Device Selection}
F -->|CPU| G[Atomic Injection]
F -->|GPU| H[Async CUDA Stream]
G --> I[Updated Model]
H --> I
end
- Atomic Injection & Zero-Downtime: SDS modifies model weights at the memory-pointer level using
torch.no_grad(), ensuring zero-drop inference. - Sparse Delta Engine: Reduces patch sizes from MBs to KBs using mathematical delta computation.
- Cryptographic Security: SHA-256 integrity handshake verifies every patch before application.
- Dual-Engine Performance: Optimized paths for both CPU (direct memory) and GPU (Async CUDA Streams).
Clone the repository to your local workspace:
git clone [https://github.com/ANSH-GIT77/synaptic-delta-sync.git](https://github.com/ANSH-GIT77/synaptic-delta-sync.git)
cd synaptic-delta-sync
The AtomicInjector class handles all the heavy lifting automatically:
from sds.core.injection import AtomicInjector
from sds.protocol.serializer import load_patch
# 1. Initialize engine
injector = AtomicInjector(model)
# 2. Load secure patch
delta, metadata, patch_hash = load_patch("updates.sds")
# 3. Apply patch
injector.apply_patch(delta, patch_hash=patch_hash)synaptic-delta-sync/
├── sds/
│ ├── core/ # Engine Logic
│ ├── hot_swap/ # Validation
│ └── protocol/ # Serialization
├── examples/ # Tests
└── pyproject.toml # Config
- v0.1.0: Core Engine & Security Validator.
- Next: Distributed Patching (RPC) & Multi-GPU sharding.
Ansh Nimbalkar | AI Infrastructure Engineer