Infrastructure

Physical hardware, system architecture, and core infrastructure components powering AI research and experimentation.

Hardware Inventory

Hardware specifications are documented in detail

For complete hardware inventory, specifications, and performance profiles, see the Hardware Inventory documentation .

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Compute Infrastructure

GPU Acceleration NVIDIA GPUs
Primary Workloads LLM Inference
Orchestration Container-based
Focus Self-hosted AI
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Storage Architecture

Hot Tier NVMe SSD
Warm/Cold Tier HDD Arrays
Use Cases Model weights, datasets
Strategy Tiered storage
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Network Topology

Internal Network 10GbE+
Design Goal Low latency
Future Expansion Multi-node clusters
Optimization Distributed workloads
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Observability Stack

Metrics Prometheus
Visualization Grafana
GPU Monitoring DCGM/nvtop
Logs Loki/structured

System Architecture

Infrastructure Layers

Hardware Layer

Physical servers, GPUs, storage arrays, networking equipment

Virtualization Layer

GPU passthrough, resource isolation, containerization (Docker/Podman)

Orchestration Layer

Workload scheduling, resource management, service deployment

Application Layer

Model serving (vLLM, Triton), data pipelines, custom tooling

Key Technologies

Model Serving

Production-grade LLM inference engines

vLLM Triton TGI

GPU Optimization

CUDA libraries and acceleration frameworks

CUDA cuBLAS Flash Attention

Data Pipeline

Processing and orchestration tools

Airflow DuckDB Parquet

Infrastructure as Code

Provisioning and configuration management

Ansible Terraform Packer

Current Infrastructure Projects

GPU Baseline Performance

Active

Establishing performance baselines for GPU compute, memory bandwidth, and thermal characteristics under sustained AI workloads.

Storage Tier Strategy

Planning

Designing hot/warm/cold storage tiers optimized for model weights, training datasets, and long-term archival.

Monitoring Stack

Active

Deploying comprehensive observability for GPU utilization, power consumption, and inference latency.

Network Optimization

Future

Planning network topology for multi-node GPU clusters and distributed inference workloads.

Infrastructure Documentation

Detailed specifications, architecture decisions, and operational runbooks are maintained in the GitHub repository.

Hardware Inventory Infrastructure Configs All Documentation