Data Parallelism

Definitions

1. A form of parallelization where the same operation is applied simultaneously to different elements of a dataset, distributing data across multiple processors. GPUs excel at data parallelism. In deep learning, data-parallel training splits batches across GPUs.

   In plain English: Splitting a big dataset across many processors so they all do the same calculation on their piece at the same time, like dividing homework among classmates.

Related Terms

• Classification
• Coforall
• Distributed Array
• Shader
• WebGPU
• Compute Shader
• Fragment Shader
• PyTorch
• Texture
• Slurm