davisking/dlib

Choose backend (GPU/CPU)

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#1,852 opened on 2019年7月31日

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 (12 comments) (1 reaction) (0 assignees)C++ (12,570 stars) (3,314 forks)batch import
enhancementhelp wanted

説明

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?

コントリビューターガイド

技術スタック
ccpppython
領域
machine learningbackend
Issue 種別
feature
難度新しい貢献者にとっての実装難度です。1 は非常に小さな変更、5 は専門的な作業です。
3
推定時間経験ある貢献者が調査、実装、テスト、pull request 準備にかけるおおよその時間範囲です。
over 1 week
活動状況Issue が今どれだけ取り組みやすいかを示します。新しい、活発、古い、ブロック中、またはメンテナー入力待ちなどです。
stale
明確さ期待される変更、受け入れ条件、次の手順がどれだけ明確かを示します。
mostly clear
前提条件
Basic understanding of dlibFamiliarity with CUDAMultithreading concepts
初心者向け度初回貢献者にどれだけ取り組みやすいかを 1-100 で推定したスコアです。
20
調査方針
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.