Choose backend (GPU/CPU) · davisking/dlib#1852

(12 留言) (1 反應) (0 負責人)C++ (12,570 star) (3,314 fork)batch import

enhancementhelp wanted

描述

So I couldn't find a way to do this in the documentation but I was wondering if there was a way to force dlib to use the CPU if it's built with CUDA enabled? I ask because I'm making a multithreaded application with dlib and only a maximum of 2 threads at a time can use CUDA (because of limitations of the GPU itself). So I'd like to in a thread get dlib to use the GPU in the thread if <2 threads are using the GPU and otherwise fallback to using the CPU.

Also a slightly related question how would dlib cope with a machine with multiple GPUs installed all for compute purposes?

貢獻者指南

技術棧: ccpppython
領域: machine learningbackend
議題類型: feature
難度: 3
預計時間: over 1 week
活動狀態: stale
清晰度: mostly clear
前置要求: Basic understanding of dlibFamiliarity with CUDAMultithreading concepts
新手友善度: 20
研究方向: The issue requests a runtime mechanism to choose between GPU and CPU execution in dlib, especially for multithreaded scenarios where GPU resource is limited. The discussion highlights the need for a thread safe fallback. To address this, one should examine dlib's CUDA integration in the source code (e.g., dlib/dnn/tensor cuda.cpp) and the threading model. Possible approaches include adding a global or thread local flag to disable CUDA or use a GPU lock. The maintainer has not provided specific guidance, so any solution would require careful design to minimize performance impact.