Tag: OCP

Redfish for AI DC

Posted on by lechuck park

This image illustrates the pivotal role of the Redfish API (developed by DMTF) as the standardized management backbone for modern AI Data Centers (AI DC). As AI workloads demand unprecedented levels of power and cooling, Redfish moves beyond traditional server management to provide a unified framework for the entire infrastructure stack.

1. Management & Security Framework (Left Column)

  • Unified Multi-Vendor Management:
    • Acts as a single, standardized API to manage diverse hardware from different vendors (NVIDIA, AMD, Intel, etc.).
    • It reduces operational complexity by replacing fragmented, vendor-specific IPMI or OEM extensions with a consistent interface.
  • Modern Security Framework:
    • Designed for multi-tenant AI environments where security is paramount.
    • Supports robust protocols like session-based authentication, X.509 certificates, and RBAC (Role-Based Access Control) to ensure only authorized entities can modify critical infrastructure.
  • Precision Telemetry:
    • Provides high-granularity, real-time data collection for voltage, current, and temperature.
    • This serves as the foundation for energy efficiency optimization and fine-tuning performance based on real-time hardware health.

2. Infrastructure & Hardware Control (Right Column)

  • Compute / Accelerators:
    • Enables per-GPU instance power capping, allowing operators to limit power consumption at a granular level.
    • Monitors the health of high-speed interconnects like NVLink and PCIe switches, and simplifies firmware lifecycle management across the cluster.
  • Liquid Cooling:
    • As AI chips run hotter, Redfish integrates with CDU (Cooling Distribution Unit) systems to monitor pump RPM and loop pressure.
    • It includes critical safety features like leak detection sensors and integrated event handling to prevent hardware damage.
  • Power Infrastructure:
    • Extends management to the rack level, including Smart PDU outlet metering and OCP (Open Compute Project) Power Shelf load balancing.
    • Facilitates advanced efficiency analytics to drive down PUE (Power Usage Effectiveness).

Summary

For an AI DC Optimization Architect, Redfish is the essential “language” that enables Software-Defined Infrastructure. By moving away from manual, siloed hardware management and toward this API-driven approach, data centers can achieve the extreme automation required to shift OPEX structures predominantly toward electricity costs rather than labor.

#AIDataCenter #RedfishAPI #DMTF #DataCenterInfrastructure #GPUComputing #LiquidCooling #SustainableIT #SmartPDU #OCP #InfrastructureAutomation #TechArchitecture #EnergyEfficiency

With Gemini

CDU ( OCP Project Deschutes ) Numbers

Posted on by lechuck park

OCP CDU (Deschutes) Standard Overview

The provided visual summarizes the key performance metrics of the CDU (Cooling Distribution Unit) that adheres to the OCP (Open Compute Project) ‘Project Deschutes’ specification. This CDU is designed for high-performance computing environments, particularly for massive-scale liquid cooling of AI/ML workloads.

Key Performance Indicators

  • System Availability: The primary target for system availability is 99.999%. This represents an extremely high level of reliability, with less than 5 minutes and 15 seconds of downtime per year.
  • Thermal Load Capacity: The CDU is designed to handle a thermal load of up to 2,000 kW, which is among the highest thermal capacities in the industry.
  • Power Usage: The CDU itself consumes 74 kW of power.
  • IT Flow Rate: It supplies coolant to the servers at a rate of 500 GPM (approximately 1,900 LPM).
  • Operating Pressure: The overall system operating pressure is within a range of 0-130 psig (approximately 0-900 kPa).
  • IT Differential Pressure: The pressure difference required on the server side is 80-90 psi (approximately 550-620 kPa).
  • Approach Temperature: The approach temperature, a key indicator of heat exchange efficiency, is targeted at ≤3∘C. A lower value is better, as it signifies more efficient heat removal.

Why Cooling is Crucial for GPU Performance

Cooling has a direct and significant impact on GPU performance and stability. Because GPUs are highly sensitive to heat, if they are not maintained within an optimal temperature range, they will automatically reduce their performance through a process called thermal throttling to prevent damage.

The ‘Project Deschutes’ CDU is engineered to prevent this by handling a massive thermal load of 2,000 kW with a powerful 500 GPM flow rate and a low approach temperature of ≤3∘C. This robust cooling capability ensures that GPUs can operate at their maximum potential without being limited by heat, which is essential for maximizing performance in demanding AI workloads.

with Gemini