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Accelerated Computing (F1)

  • What it is
    • Uses hardware accelerators (co-processors) to do work more efficiently than software on CPU.
    • You pay for the accelerator, so only use it when the workload can actually exploit it.
  • F1 specifically
    • Field Programmable Gate Arrays (FPGAs) — hardware you reprogram for a custom algorithm.
    • For genomics, financial analytics, real-time video processing, custom hardware acceleration.
  • The other accelerated families
    • P / G — NVIDIA GPUs. P for ML training, G for graphics and inference.
    • Trn — AWS Trainium, purpose-built for training large models.
    • Inf — AWS Inferentia, purpose-built for cheap high-throughput inference.
  • Not to be confused with

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