Intel Tiber Cloud Deployment

Deploy TrustGraph on Intel Tiber Cloud with Intel GPU and Gaudi accelerated systems for high-performance AI workloads.

Overview

TrustGraph provides specialized deployment configurations for Intel’s advanced hardware platforms, including Intel Tiber Cloud and bare-metal Intel GPU/Gaudi systems. This deployment method is designed for:

  • High-performance AI inference with Intel accelerators
  • Self-hosted deployments on Intel hardware
  • Research and development with cutting-edge Intel AI technologies
  • Enterprise workloads requiring Intel-optimized performance

⚠️ Work in Progress: This deployment method is actively being developed and optimized for Intel’s latest hardware platforms.

What You Get

The Intel Tiber Cloud deployment includes:

  • Intel accelerated systems (Gaudi, GPU, or GR platforms)
  • Optimized AI inference with vLLM or TGI servers
  • Large language models like Llama 3.3 70B
  • Complete TrustGraph stack deployed via containerization
  • SSH-based deployment with automated scripts
  • Port forwarding setup for secure access
  • Monitoring and observability with Grafana
  • Web workbench for document processing and Graph RAG

Intel Hardware Platforms

Intel Gaudi Systems

  • Software: TrustGraph 1.0.13 + vLLM (HabanaAI fork)
  • Model: Llama 3.3 70B
  • Deployment: deploy-gaudi-vllm.zip
  • Optimized for: AI training and inference workloads

Intel GPU Multi-GPU 1550 Systems

  • Software: TrustGraph 1.0.13 + TGI Server 3.3.1-intel-xpu
  • Deployment: deploy-gpu-tgi.zip
  • Optimized for: High-throughput GPU inference

Intel GR Systems

  • Software: TrustGraph 1.0.13 + TGI Server 3.3.1-intel-xpu
  • Deployment: deploy-gr.zip
  • Optimized for: Specialized Intel AI workloads

Why Choose Intel Tiber Cloud?

🚀 Cutting-Edge AI Hardware

  • Intel Gaudi: Purpose-built for AI training and inference
  • Intel GPU: High-performance parallel processing
  • Specialized Architecture: Optimized for AI/ML workloads

⚡ Performance Optimization

  • Hardware-Accelerated Inference: Native Intel optimization
  • Large Model Support: Handle models like Llama 3.3 70B efficiently
  • Reduced Latency: Direct hardware acceleration

🔒 Self-Hosted Control

  • Data Sovereignty: Complete control over data and models
  • Custom Configuration: Tailor deployments to specific needs
  • Enterprise Security: Self-hosted infrastructure

🛠️ Developer Access

  • Research Platform: Access to latest Intel AI technologies
  • Experimentation: Test advanced AI configurations
  • Direct Hardware Access: Low-level optimization capabilities

Deployment Method

The Intel deployment uses automated deployment scripts that:

  • Connect via SSH jump host to Intel Tiber Cloud
  • Deploy pre-configured TrustGraph packages
  • Set up Intel-optimized AI inference servers
  • Configure port forwarding for secure access
  • Initialize monitoring and web interfaces

Quick Process Overview

  1. Obtain access to Intel Tiber Cloud instance
  2. Create HuggingFace token and accept model licenses
  3. Choose deployment type (Gaudi, GPU, or GR)
  4. Deploy via script with SSH parameters
  5. Connect via SSH with port forwarding
  6. Access services through forwarded ports

Access Configuration

Intel Tiber Cloud uses SSH jump host access:

# SSH connection format
ssh -J guest@[jump-host] sdp@[target-host]

# Deployment command
./deploy-tiber guest@[jump-host] sdp@[target-host] [deployment-package]

# Port forwarding
./port-forward guest@[jump-host] sdp@[target-host]

Access Points

Once deployed, you’ll have access to:

  • TrustGraph API: Port 8089 (forwarded from 8088)
  • Web Workbench: Port 8889 (forwarded from 8888)
  • Grafana Monitoring: Port 3001 (forwarded from 3000)

Model Support

Large Language Models: Llama 3.3 70B and other HuggingFace models License Requirements: HuggingFace account with model access Hardware Optimization: Intel-specific optimizations for inference Inference Engines: vLLM (Gaudi) and TGI (GPU/GR)

Complete Documentation

For detailed step-by-step instructions, deployment packages, and troubleshooting, visit:

TrustGraph Intel Tiber Cloud Guide

The repository contains:

  • Deployment automation scripts
  • Intel platform-specific configurations
  • Pre-built deployment packages
  • SSH connection utilities
  • Port forwarding setup
  • Detailed setup instructions
  • Intel hardware optimization guides

Prerequisites

Intel Tiber Cloud Access: Account and instance allocation HuggingFace Token: For model downloads and licensing SSH Access: Familiarity with SSH jump host connections Model Licenses: Acceptance of required model licenses (e.g., Llama)

Performance Benefits

Hardware Acceleration: Native Intel AI acceleration Large Model Efficiency: Optimized for 70B+ parameter models Reduced Infrastructure Costs: Efficient hardware utilization Custom Optimization: Direct access to hardware-level tuning

Use Cases

Research & Development: Access to cutting-edge Intel AI hardware High-Performance Inference: Large model deployment with optimal performance Self-Hosted AI: Complete control over AI infrastructure Intel Ecosystem Integration: Leverage Intel’s AI software stack

Next Steps

After deployment, you can:

  • Load documents through the web workbench
  • Test Graph RAG queries with Llama 3.3 70B
  • Monitor Intel hardware performance through Grafana
  • Experiment with Intel-optimized AI configurations
  • Benchmark performance against other platforms
  • Integrate with Intel’s AI development tools