Tag: Operation

GPU Server Room : Changes

Posted on by lechuck park

Image Overview

This dashboard displays the cascading resource changes that occur when GPU workload increases in an AI data center server room monitoring system.

Key Change Sequence (Estimated Values)

  1. GPU Load Increase: 30% → 90% (AI computation tasks initiated)
  2. Power Consumption Rise: 0.42kW → 1.26kW (3x increase)
  3. Temperature Delta Rise: 7°C → 17°C (increased heat generation)
  4. Cooling System Response:
    • Water flow rate: 200 LPM → 600 LPM (3x increase)
    • Fan speed: 600 RPM → 1200 RPM (2x increase)

Operational Prediction Implications

  • Operating Costs: Approximately 3x increase from baseline expected
  • Spare Capacity: 40% cooling system capacity remaining
  • Expansion Capability: Current setup can accommodate additional 67% GPU load

This AI data center monitoring dashboard illustrates the cascading resource changes when GPU workload increases from 30% to 90%, triggering proportional increases in power consumption (3x), cooling flow rate (3x), and fan speed (2x). The system demonstrates predictable operational scaling patterns, with current cooling capacity showing 40% remaining headroom for additional GPU load expansion. Note: All values are estimated figures for demonstration purposes.

Note: All numerical values are estimated figures for demonstration purposes and do not represent actual measured data.

With Claude

Basic Power Operations

Posted on by lechuck park

This image illustrates “Basic Power Operations,” showing the path and processes of electricity flowing from source to end-use.

The upper diagram includes the following key components from left to right:

  • Power Source/Intake – High voltage for efficient delivery with high warning
  • Transformer – Performs voltage step-down
  • Generator and Fuel Tank – Backup Power
  • Transformer #2 – Additional voltage step-down
  • UPS/Battery – 2nd Backup Power
  • PDU/TOB – Supplies power to the final servers

The diagram displays two backup power systems:

  • Backup power (Full outage) – Functions during complete power failures with backup time provided by Oil Tank with Generators
  • Backup Power (Partial outage) – Operates during partial outages with backup time provided by the Battery with UPSs

The simplified diagram at the bottom summarizes the complex power system into these fundamental elements:

  1. Source – Origin point of power
  2. Step-down – Voltage conversion
  3. Backup – Emergency power supply
  4. Use – Final power consumption

Throughout all stages of this process, two critical functions occur continuously:

  • Transmit – The ongoing process of transferring power that happens between and during all steps
  • Switching/Block – Control points distributed throughout the system that direct, regulate, or block power flow as needed

This demonstrates that seemingly complex power systems can be distilled into these essential concepts, with transmission and switching/blocking functioning as integral operations that connect and control all stages of the power delivery process.

WIth Claude

Operation with LLM

Posted on by lechuck park

This image is a diagram titled “Operation with LLM,” showing a system architecture that integrates Large Language Models (LLMs) with existing operational technologies.

The main purpose of this system is to more efficiently analyze and solve various operational data and situations using LLMs.

Key components and functions:

  1. Top Left: “Monitoring Dashboard” – Provides an environment where LLMs can interpret image data collected from monitoring screens.
  2. Top Center: “Historical Log & Document” – LLMs analyze system log files and organize related processes from user manuals.
  3. Top Right: “Prompt for chatting” – An interface for interacting with LLMs through appropriate prompts.
  4. Bottom Left: “Image LLM (multimodal)” – Represents multimodal LLM functionality for interpreting images from monitoring screens.
  5. Bottom Center: “LLM” – The core language model component that processes text-based logs and documents.
  6. Bottom Right:
    • “Analysis to Text” – LLMs analyze various input sources and convert them to text
    • “QnA on prompt” – Users can ask questions about problem situations, and LLMs provide answers

This system aims to build an integrated operational environment where problems occurring in operational settings can be easily analyzed through LLM prompting and efficiently solved through a question-answer format.

With Claude

Operation with system

Posted on by lechuck park

Key Analysis of Operation Cost Diagram

This diagram illustrates the cost structure of system implementation and operation, highlighting the following key concepts:

  1. High Initial Deployment Cost: At the beginning of a system’s lifecycle, deployment costs are substantial. This represents a one-time investment but requires significant capital.
  2. Perpetual Nature of Operation Costs: Operation costs continue indefinitely as long as the system exists, making them a permanent expense factor.
  3. Components of Operation Cost: Operation costs consist of several key elements:
    • Energy Cost
    • Labor Cost
    • Disability Cost
    • Additional miscellaneous costs (+@)
  4. Role of Automation Systems: As shown on the right side of the diagram, implementing automation systems can significantly reduce operation costs over time.
  5. Timing of Automation Investment: While automation systems also require initial investment during the early phases, they deliver long-term operation cost reduction benefits, ultimately improving the overall cost structure.

This diagram effectively visualizes the relationship between initial costs and long-term operational expenses, as well as the cost optimization strategy through automation.

With Claude

Operation

Posted on by lechuck park

With a Claude’s Help

  1. Normal State:
  • Represented by a gear icon with a green checkmark
  • Indicates system operating under normal conditions
  • Initial state of the monitoring process
  1. Anomaly Detection:
  • Shown with a magnifying glass and graph patterns
  • The graph patterns are more clearly visualized than before
  • Represents the phase where deviations from normal patterns are detected
  1. Abnormal State:
  • Depicted by a human figure with warning indicators
  • Represents confirmed abnormal conditions requiring intervention
  • Links directly to action steps
  1. Analysis and Response Process:
  • Comparison with normal: Shown through A/B document comparison icons
  • Analysis: Data examination phase
  • predictive Action: Now written in lowercase, indicating predicted response measures
  • Recovery Action: Implementation of actual recovery measures
  1. Learning Feedback:
  • Shows how lessons from recovery actions are fed back into the system
  • Creates a continuous improvement loop
  • Connects recovery actions back to normal operations

The workflow continues to effectively illustrate the complete operational cycle, from monitoring and detection through analysis, response, and continuous learning. It demonstrates a systematic approach to handling operational anomalies and maintaining system stability.

DC OP Platform

Posted on by lechuck park

From Claude with some prompting
This image depicts a diagram of the “DC op Platform” (Data Center Operations Platform). The main components are as follows:

  1. On the left, there’s “DC Op Env.” (Data Center Operations Environment), which consists of three main parts:
    • DCIM (Data Center Infrastructure Management)
    • Auto Control
    • Facility These three elements undergo a “Standardization” process.
  2. In the center, there are two “Standardization” server icons, representing the standardization process of the platform.
  3. On the right, there’s the “Data Center Op. Platform”, which comprises three main components:
    • Service Development
    • Integrated operations
    • Server Room Digital Twin
  4. Arrows show how the standardized elements connect to these three main components.

This diagram visually illustrates how the data center operations environment evolves through a standardization process into an integrated data center operations platform.