Infrastructure Services
Bare-Metal GPU Clusters
Purpose-built GPU compute clusters featuring NVIDIA H100 and B200 nodes with liquid cooling, 400Gbps InfiniBand interconnect, and NVMe-oF distributed storage. Available in 8-GPU, 64-GPU, and 256-GPU configurations with dedicated power and cooling. Provisioned through an API and ready for training in under an hour.
High-Speed Training Fabric
A full-bisection InfiniBand network fabric optimized for NCCL all-reduce operations with deterministic sub-microsecond port-to-port latency. Includes managed RDMA configuration, GPU-direct storage paths, and optional hardware-level traffic monitoring for profiling distributed training bottlenecks.
ML-Optimized Storage Platform
A distributed storage layer purpose-built for ML workloads: high-throughput parallel reads for data loading, low-latency checkpoint writes for fault tolerance, and petabyte-scale capacity for dataset management. Supports POSIX, S3-compatible, and GPU-direct access patterns.
GPU Cluster Orchestration
A managed orchestration layer built on Kubernetes with GPU-aware scheduling, automatic NCCL topology detection, elastic training support, and preemption-aware job queuing. Integrates with PyTorch, JAX, and DeepSpeed out of the box.
Disaster Recovery & Checkpoint Management
Geographically redundant checkpoint storage with automated replication and point-in-time recovery. Resume interrupted training runs from the last checkpoint within minutes, not hours. Designed for multi-day training jobs where losing progress is measured in GPU-hours and dollars.
Infrastructure Consulting
Hands-on architecture reviews, training pipeline optimization, and GPU cluster design engagements delivered by engineers who have built infrastructure for some of the world's largest ML training operations. Includes NCCL tuning, data pipeline profiling, and facility design.