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Machine Learning Engineering Open Book

48 / 52·markdown

文档

01Machine Learning Engineering Open Book
42Contributors
44Machine Learning Engineering
52TODO

insights

02The AI Battlefield Engineering - What You Need To Know
03How to Choose a Cloud Provider
04When Is It Worth Upgrading GPUs?

compute

05Compute
06Accelerators
07Accelerator Benchmarks
08Troubleshooting NVIDIA GPUs
09Troubleshooting AMD GPUs
10AMD GPUs Performance
11CPU
12CPU Memory

storage

13Storage: File Systems and IO

network

14Inter-Node and Intra-Node Networking Hardware
15Communication Patterns
16Network Debug
17Networking Benchmarks

orchestration

18Orchestration
19Working in SLURM Environment
20SLURM Administration
21SLURM for Users
22SLURM Performance
23Single and Multi-Node Launchers with SLURM
24Kubernetes

training

25Training
26Model Parallelism
27Software Tune Up For The Best Performance
28Fault Tolerance
29Reproducibility
30Avoiding, Recovering From and Understanding Instabilities
31Understanding Training Loss Patterns
32Checkpoints
33Selecting Training Hyper-Parameters And Model Initializations
34Tensor Precision / Data Types
35Emulate a Multi-Node Setup Using Just a Single Node
36Re-Train HF Hub Models From Scratch Using Finetuning Examples

inference

37Inference

debug

38Debugging and Troubleshooting
39Debugging PyTorch Programs
40A Backup of Scripts
45Faster Debug and Development with Tiny Models, Tokenizers and Datasets
46NCCL: Debug and Performance
47Diagnosing Hangings and Deadlocks in Multi-Node Multi-GPU Python Programs
48Underflow and Overflow Detection

testing

41Writing and Running Tests

courses

43Lessons Learned from Training LLMs (a course)

model parallelism

49Model Parallelism

stabs

50Stabs
51Things to add / integrate

Chapter 48

Underflow and Overflow Detection

Underflow and Overflow Detection

Moved to Debugging PyTorch Programs.

Specific batch absolute min and max value tracing

Moved to Debugging PyTorch Programs.

上一章

Diagnosing Hangings and Deadlocks in Multi-Node Multi-GPU Python Programs

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Model Parallelism

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