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Understanding High Performance Computing on Google Cloud

May 9, 2025

Google Cloud Drawing Board: High Performance Computing (HPC)

Introduction to HPC

  • Definition: HPC is the aggregation of computing power to solve large-scale problems that standard computers cannot handle efficiently.
  • Also Known As: Supercomputing.
  • Purpose: Enables simulation or analysis of huge data volumes.
  • Challenges:
    • Producing or processing more data than infrastructure can handle.
    • Delays in results can hinder innovation and research.

HPC System Overview

  • Structure: Comprises a group of computers known as a cluster.
  • Components:
    • Each computer in a cluster is called a node.
    • A node includes an OS, processor (with multiple cores), storage, and networking capabilities.
  • Example: A small cluster has 16 nodes with 64 cores.
  • Supercomputer: A large variation of HPC with significant processing capability.

HPC with Google Cloud

  • Advantages:
    • Access to extensive compute and storage hardware.
    • Global presence and robust networking.
    • Intelligent management capabilities.
    • Cost efficiency, especially in the cloud environment.
  • Example: HPC job reduced from 3 months on-premises to 16 hours in the cloud with 125,000 cores.

Building HPC Environment on Google Cloud

Compute Components

  • Compute Engine: Offers customizable virtual machines.
    • Machine Types:
      • Compute optimized (C2) for most applications.
      • General purpose (N1, N2, N2D) for larger memory.
      • A2 instances for GPU requirements.
    • Customization: Allows specific cores and memory matching.
    • Preemptable VMs: Cost-effective for batch jobs and fault-tolerant workloads.

Storage Options

  • Cloud Storage: Scalable object store for large data volumes.
  • Persistent Disk: Durable, high-performance block storage.
  • File Store High Scale: High-performance file system for easy file sharing.

Networking Infrastructure

  • Global Network: Managed network infrastructure for limited internet exposure.
  • Virtual Private Cloud (VPC): Enables connectivity and firewall configurations.
  • Placement Policies:
    • Compact Placement Policy: Ensures low latency between nodes by optimizing instance placement.

Putting it All Together

  1. Determine Requirements: Assess compute, storage, and networking needs.
  2. Create Cluster: Use Compute Engine instances with selected storage.
  3. Job Scheduling: Use Google Cloud’s job schedulers for auto-scaling and cost management.
  4. Post Processing: Visualize results using BigQuery or AI platform.
  5. Monitor and Adjust: Continuously monitor performance and make necessary adjustments.

Security in HPC

  • Google Cloud Security: Secure by design infrastructure with advanced threat detection.

Applications of HPC

  • Industries:
    • Film (visual effects rendering).
    • Genomics (human genome sequencing).
    • Financial Services (risk analysis).
    • Automotive (car design).

Conclusion

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