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GPU Compute Overview

The lab uses a mixed GPU strategy for practical, daily-use AI workloads.

Compute Tiers​

  • High-throughput tier: large discrete GPUs for heavier inference and media/AI workloads
  • Distributed light tier: integrated GPUs for lighter, parallelizable jobs (for example embedding pipelines)

Workload Strategy​

  • Use heavyweight GPUs for quality-critical or latency-sensitive tasks
  • Use lighter nodes for scheduled/background processing
  • Keep interfaces stable so backends can evolve without rewriting application logic

Current Direction​

  • Local documentation retrieval pipeline with search API and citations
  • Embedding backends designed to be swappable via service interface
  • Follow-up automation to reduce operational stall between decisions and execution

Security and Publication​

Public-facing documentation describes capabilities and patterns, not sensitive operational internals.