✳flâneur — a map of the web's best reading

GPU Performance Background User's Guide - NVIDIA Docs

docs.nvidia.com · 3,785 words · saved by 2 readers

This guide provides background on the structure of a GPU, how operations are executed, and common limitations with deep learning operations. It is helpful to understand the basics of GPU execution when reasoning about how efficiently particular layers or neural networks are utilizing a given GPU. This guide describes: The basic structure of a GPU (GPU Architecture Fundamentals) How operations are divided and executed in parallel (GPU Execution Model) How to estimate performance limitations with arithmetic intensity (Understanding Performance) Loose categories of deep learning operations and the performance limitations that tend to apply to each (DNN Operation Categories) The GPU is a highly parallel processor architecture, composed of processing elements and a memory hierarchy. At a high level, NVIDIA® GPUs consist of a number of Streaming Multiprocessors (SMs), on-chip L2 cache, and high-bandwidth DRAM. Arithmetic and other instructions are executed by the SMs; data and code are acces

GPU Performance Background User's Guide - NVIDIA Docs Menu Docs Hub NVIDIA Deep Learning Performance Submit Search Submit Search NVIDIA Docs Hub Homepage Deep Learning Performance NVIDIA Deep Learning Performance GPU Performance Background User's Guide Download PDF GPU Performance Background User's Guide Abstract This guide provides background on the structure of a GPU, how operations are executed, and common limitations with deep learning operations. 1. Overview It is helpful to understand the basics of GPU execution when reasoning about how efficiently particular layers or neural networks ar

Explore this link on the map →

saved by

related reading