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This document helps you optimize Goodput, the rate of useful data
transferred, for your workloads. To achieve this optimization, we have curated
reproducible Goodput recipes that use common machine learning (ML) frameworks
and models. To review these recipes, see the
AI Hypercomputer GitHub organization.
Before you begin
Before you use the Goodput recipes in this document, complete the following
steps if you haven't already:
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-04-12 UTC."],[[["This document provides Goodput optimization strategies for workloads, focusing on the rate of useful data transfer."],["Reproducible Goodput recipes, tested on clusters using Cluster Toolkit, are available within the AI Hypercomputer GitHub organization."],["The document guides users through selecting an accelerator, choosing a consumption method, and creating a cluster, all before using the provided recipes."],["A pre-training recipe for Llama3.1 70B using the NeMo framework on A3 Mega accelerators in GKE clusters is available."]]],[]]
