GPU Allocation Optimizer
MNT-LO allocates GPU workloads with microsecond-scale latency and zero conflicts. A black-box deterministic engine — proprietary, production-ready, measurable.
Per-workload allocation decision. 20,000 workloads processed in 123ms — validated across 3 consecutive benchmark runs.
Stranded GPU memory reclaimed during a live large-scale cluster simulation — eliminating residual topological fragmentation.
Zero constraint violations. Zero corrupted GPU nodes. RCRS 100% across all tested configurations.
Send a JSON payload describing your GPU resources, workload constraints, and allocation preferences. No configuration files, no training data, no warm-up.
MNT-LO's proprietary deterministic engine resolves the allocation internally. No randomness, no heuristics — the same input always produces the same optimal output.
Receive a clean allocation map in microseconds. Each GPU assigned, zero conflicts, ready to deploy. Integrate directly into your orchestration pipeline.
Deployed as a high-performance, stateless Docker container. Native Linux integration designed to secure IP privacy with zero system overhead.
{
"nodes": [
{ "id": "gpu-01", "mem_gb": 80, "type": "H100" },
{ "id": "gpu-02", "mem_gb": 40, "type": "A100" }
],
"workloads": [
{ "id": "job-001", "mem_gb": 40, "priority": "high" },
{ "id": "job-002", "mem_gb": 24, "priority": "normal" }
]
}
{
"allocations": [
{ "workload": "job-001", "gpu": "gpu-01", "score": 1.0, "type": "best_fit" },
{ "workload": "job-002", "gpu": "gpu-02", "score": 1.0, "type": "best_fit" }
],
"vram_residual_gb": 0,
"latency_ms": 0.25,
"sla_level": "platinum",
"deterministic": true
}
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