NVIDIA A100-SXM4-80GB
AssessPlatforms
A data center GPU used here as the execution hardware for profiling experiments.
Why it's here
Placed in Assess: 2 article(s) of evidence from 1 source(s), led by research-stage coverage, with 0 in the last 30 days. Confidence 32%.
Evidence (2)
- 3Hugging Face Blog·6/11/2026researchProfiling PyTorch Linear Layers and Fused MLPs
This Hugging Face blog post continues a series on reading PyTorch profiler traces, focusing on replacing a manual matmul-plus-bias pattern with nn.Linear and then stacking layers into an MLP. It explains how PyTorch handles transposition, addmm, and kernel launches, and uses profiling to motivate performance optimizations such as fused MLPs.
- 4Hugging Face Blog·5/29/2026framework_updateA Beginner’s Guide to torch.profiler in PyTorch
Hugging Face Blog introduces the first part of a series on profiling in PyTorch, focused on helping beginners read profiler traces and understand how Python calls map to CPU and CUDA activity. The article explains how to use torch.profiler, interpret its tables and traces, and observe what changes when torch.compile is applied.