Distributed Training and AI Hardware

GPUs, accelerators, parallelism and the infrastructure behind large models.

AI-480 Year 4 3 credits 5 lessons planned

Offered by HSM University · Artificial Intelligence

Course content

  1. 1GPU and accelerator architectureComing
  2. 2Data, tensor and pipeline parallelismComing
  3. 3Memory and numerical precisionComing
  4. 4Clusters, networking and storageComing
  5. 5Energy and compute economicsComing

Requirements

Recommended background. You can start any course at any time.

Description

GPUs, accelerators, parallelism and the infrastructure behind large models.

Part of the Science stream, typically taken in year 4.