Unified monitoring for heterogeneous resources. Observe the status of diverse infrastructure hardware (nodes, network, storage, GPU, power equipment, and more) in one place, and deliver the key data each audience needs — operators, users, and finance teams — tailored to their role.
01WHAT WE FIX
The challenges clients bring to us.
01
Our GPU cluster utilization is stuck in the 30% range
We redesign queue policy, workload analysis, and Luxe Vision monitoring together to raise it to over 70% on average. A 4–6 month project.
02
Multi-vendor integration responsibility is fragmented
One team owns servers, storage, network, and scheduler end to end. You never get caught between vendors, and every line of responsibility is clear.
03
The cluster we built doesn't deliver the performance in the spec
We trace NCCL, MPI, storage IO, fabric topology, and firmware together to eliminate bottlenecks in one pass.
02SOLUTIONS
A design approach for every workload.
We start with vendor-neutral consulting and close the loop with the Luxe Series at the operations stage.
CPU · MPI
HPC Cluster Design
CPU supercomputer design for large-scale MPI-based simulation — CFD, molecular dynamics, weather, quantum chemistry, and more — built on the latest architectures (Sapphire Rapids · Granite Rapids · EPYC), with NUMA topology optimization, balanced memory bandwidth, and fat-tree InfiniBand fabric.
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GPU · NCCL
AI Supercomputer
LLM training and inference clusters on NVIDIA H100 · H200 · B200 · B300 or AMD MI300X — rail-optimized fat-tree topology, 95%+ NCCL AllReduce efficiency, NVMe-oF checkpoint IO, and guaranteed 80%+ training GPU utilization.
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Spectrum Scale · Lustre · BeeGFS · VAST
Parallel Storage
TB/s-class parallel file systems on IBM Spectrum Scale · Lustre · BeeGFS · VAST Data · DAOS — separated metadata and data NSDs, AFM DR cache, and 1.2M ops/s small-file metadata throughput for AI training.
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IB · RoCE
Interconnect
High-performance network fabrics on InfiniBand XDR 800Gbps · NDR 400Gbps or RoCEv2 — non-blocking fat-tree (4 spine × 6 leaf), adaptive routing, and 95%+ efficiency against spec on MPI and NCCL collectives.
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Slurm · K8s
Schedulers
Hybrid Slurm + Kubernetes operations (Volcano · Run:ai · GPU Operator) — time-based partitioning of a shared GPU pool, with queue policy, backfill, FairShare, and multi-tenancy quotas all designed together.
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Reference
Application Workload
Reference architectures by domain (CFD · MD · weather · LLM training · inference · HPDA) published together with measurement assumptions and performance figures — the starting point for RFPs and decision-making.
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03LUXE SERIES
Four layers of operations, four products from one company.
From heterogeneous hardware telemetry to user-facing visualization — all running on a unified data model and a single operational accountability.
View the full Luxe Series →4-LAYER STACK
L1Luxe VisionUnified Monitoring
L2Luxe RayOperations & Unified Control
L3Luxe VantageUsage & Billing Cloud
L4Luxe OrbitSW Provisioning & Parallel Management


