SLIPSTREAM

Speculative Orchestrator for Ollama & Llama.cpp

投機的オーケストレーター

🇯🇵 Made in Japan (日本製)

Dynamic multi-instance orchestration engineered to handle high-velocity speculative decoding, routing, and memory teardown directly at the hardware edge.

ハードウェアエッジで高速度の投機的デコーディング、ルーティング、メモリティアドOWNを処理するように設計された動的マルチインスタンスオーケストレーション。

Core Architecture

コアアーキテクチャ

⚡

High-Velocity Speculative Decoding

高速度投機的デコーディング

Engineered for maximum throughput with intelligent token prediction and verification pipelines that minimize latency at the hardware level.

🔀

Dynamic Instance Routing

動的インスタンスルーティング

Real-time workload distribution across multiple LLM instances.

🧠

Memory Teardown Engine

メモリティアドOWNエンジン

Aggressive memory reclamation and context management to maintain optimal performance during high-concurrency operations.

🔗

Ollama & Llama.cpp Integration

Ollama & Llama.cpp統合

Seamless orchestration layer for existing LLM inference frameworks. Drop-in enhancement without code modifications.

📊

Hardware-Edge Deployment

ハードウェアエッジデプロイメント

Zero cloud dependencies. Designed for on-premise and edge computing environments with strict sovereignty requirements.

🔒

Sovereign Intelligence

主権AI

Full architectural control. No external telemetry, no data leakage, complete operational transparency for audit-critical deployments.

Terminal Captures

ライブターミナルキャプチャ

Dual RTX 3060 at 24GB VRAM total
Dual RTX 3060 at 24GB VRAM total GTX 1070 at 8GB VRAM AMD iGPU 16GB Unified RAM AMD iGPU 16GB Unified RAM GTX 1070 at 8GB VRAM

Architecture Notes

アーキテクチャノート

⚠️

Garbage Collection & Draft Models

ガベージコレクションとドラフトモデル

When utilizing Slipstream's dynamic // DRAFT_MODEL tags for speculative decoding, be aware of current backend limitations. Ollama's native garbage collector does not cryptographically trace these dynamic dependency links.

Admin Warning: Running aggressive blob pruning operations on the host can result in the accidental deletion of draft models tethered via Slipstream. Native dependency checking will be available in future releases of the slip inspect feature.

💾

VRAM Edge Allocation Thresholds

VRAMエッジ割り当てのしきい値

Operating near the absolute ceiling of hardware memory capacity introduces severe instability in standard inference backends. Dynamic context expansion and backend execution overhead can trigger fatal cudaMalloc Out-Of-Memory (OOM) failures.

Slipstream Mitigation: The slip inspect reports these memory spikes when they occur during hardware allocation. To maximize context windows on constrained edge nodes, enforcing Q4_0 KV cache compression (the default) is highly recommended to maintain buffer stability while reducing the triggering of runtime crashes.

⚓ The Slipstream Vessel ⚓

スリップストリーム号

"Where are you going?"
「どこへ向かっているのか?」