Distributed AI Systems

8

Running Distributed Training with SLURM

Managing GPU resources and coordinating multi-node jobs with SLURM

 

In a room full of top software designers, if two agree on the same thing, that's a majority.

Bill Curtis

Introduction to clusters for HPC and AI training

The previous chapters covered the theory and implementation of distributed training—DDP for gradient synchronization, FSDP for memory efficiency, DeepSpeed for ZeRO optimization, and Megatron for model parallelism. But understanding these frameworks is only half the challenge. The other half is actually running them on real hardware: allocating GPUs across nodes, coordinating processes, managing job queues, and handling the inevitable failures that occur at scale.

Modern AI training ...