Status: Private Alpha | Target: $1B+ Acquisition
Owner: Dante Bullock, Sovereign Logic
SINGULARITY is a Distributed Virtual Memory Manager (DVMM) for AI compute. It decouples the Model Weights (static, loaded once) from the KV-Cache/Context (dynamic, fluid) across a GPU cluster. The result: GPU utilization jumps from 25% to 85%, and "Cold Start" latency drops from 60-120 seconds to <50ms.
The arbitrage: Companies are burning 60-70% of their GPU spend on idle overhead because Kubernetes can't handle "Flash-Compute" (dynamic, spiking agent workloads). SINGULARITY turns a GPU cluster into a single, fluid memory pool.
┌─────────────────────────────────────────────────────────────┐
│ SINGULARITY STACK │
├─────────────────────────────────────────────────────────────┤
│ Python SDK: `import singularity` │
│ (singularity-python/) │
├─────────────────────────────────────────────────────────────┤
│ Predictive Oracle (CLOSED SOURCE): Sparse Attention Router │
│ (singularity-oracle/) │
├─────────────────────────────────────────────────────────────┤
│ Transport Layer (OPEN SOURCE): RDMA/RoCE v2 Fabric │
│ (singularity-transport/) │
├─────────────────────────────────────────────────────────────┤
│ vLLM Connector: Native KVConnector Backend │
│ (singularity-core/) │
├─────────────────────────────────────────────────────────────┤
│ Hardware: H100/A100 GPUs + InfiniBand/RoCE v2 │
└─────────────────────────────────────────────────────────────┘
Moving 16GB of KV-cache takes ~320ms over 400Gbps (physics). Our solution:
- Head-First Protocol: Identify the 12% of KV-cache blocks that contain 85% of attention weight
- Teleport the Head: Move 128-256MB in <5ms via RDMA
- Lazy Stream: Background-load the remaining 88% while generation runs
- Result: Perceived cold start <50ms, actual throughput = 26x faster
| Tier | What | License |
|---|---|---|
| Community | Transport layer, basic KV Connector, daemon | Apache 2.0 |
| Enterprise | Predictive Oracle, Sparse Teleportation, Dashboard | Proprietary |
Exit Strategy: Sell to CoreWeave/Lambda Labs (GPU clouds bleeding on idle H100s) or Microsoft Azure (win the cloud war). Show them 40% GPU waste recovery = $200M+/year OpEx savings.
singularity-core/ — vLLM Native KVConnector (C++/Python, open source)
singularity-transport/ — RDMA/RoCE v2 fabric (Rust, open source)
singularity-oracle/ — Sparse Attention Router (Rust, CLOSED SOURCE)
singularity-python/ — Python SDK (pip install singularity)
scripts/ — Benchmarks, deployment
docs/ — Architecture, API docs
"We decoupled Thought (Session Context) from Brain (GPU Weights). You're treating H100s like 1990s mainframes. We turn them into a Global Memory Fabric. We are the OS for the Sovereign AI Era."