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How can I oblige tensorflow to use all gpu power?
TensorFlow, a popular open-source machine learning library, is designed to automatically utilize the available GPU resources on a device. By default, TensorFlow will use all available GPU resources when training or running a model.
Tensorflow Interview Questions and Answers
However, there are a few things you can do to ensure that TensorFlow is using all of the GPU resources available:
- Set the GPU memory growth option: TensorFlow allows you to set a flag to control the GPU memory growth. You can set the flag by using the following command:
import tensorflow as tf
physical_devices = tf.config.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True)
- Limit the number of CPU threads: By default, TensorFlow will use all available CPU threads, which can limit the amount of GPU resources available. You can set the number of CPU threads that TensorFlow should use by using the following command:
import os
os.environ["OMP_NUM_THREADS"] = "4"
- Ensure that you have the latest Tensorflow version and GPU drivers: Newer Tensorflow versions includes more optimized GPU utilization, the same goes for the GPU driver, making sure that you have the latest version of both of them could help boost your GPU performance.
- Manage GPU resources with CUDA: if you’re using CUDA with Tensorflow you can use CUDA streams to synchronize and manage multiple GPU resources.
It’s worth noting that even if TensorFlow is using all available GPU resources, the performance of your model may still be limited by other factors such as the amount of data, the complexity of the model, and the number of training iterations.
It’s also important to mention that to ensure the best performance it’s always best to measure and test your model with different settings and configurations, depending on the specific use-case and dataset.

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- The C++ Programming Language (3rd edition) by Stroustrup
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- Computer Systems - A Programmer's Perspective
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin
- Growing Object-Oriented Software, Guided by Tests
- Framework Design Guidelines by Brad Abrams
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- Advanced Programming in the UNIX Environment by W. Richard Stevens
- Hackers and Painters: Big Ideas from the Computer Age
- The Soul of a New Machine by Tracy Kidder
- CLR via C# by Jeffrey Richter
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- Alice in Wonderland by Lewis Carol
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig
- About Face - The Essentials of Interaction Design
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky
- The Tao of Programming
- Computational Beauty of Nature
- Writing Solid Code by Steve Maguire
- Philip and Alex's Guide to Web Publishing
- Object-Oriented Analysis and Design with Applications by Grady Booch
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- The Art of Deception by Kevin Mitnick
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- Smalltalk-80: The Language and its Implementation
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