Best Nvidia eGPU for Basic Deep Learning on a 2017 MacBook Pro

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Summary: Explore the best Nvidia eGPU options for running basic deep learning tasks on a 2017 MacBook Pro with macOS Mojave. Enhance your TensorFlow projects and improve performance.
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Best Nvidia eGPU for Basic Deep Learning on a 2017 MacBook Pro

If you're working with deep learning on a 2017 MacBook Pro, you might have noticed that the built-in resources can fall short. Deep learning can be quite resource-intensive, especially when running applications like TensorFlow. To alleviate this, an external GPU (eGPU) can be a game-changer. In this guide, we'll explore some Nvidia eGPU options that can elevate your deep learning experience on macOS Mojave.

Why Use an eGPU?

Performance Enhancement:
Nvidia eGPUs can drastically improve the computational power of your MacBook Pro. This enhancement is particularly useful for tasks requiring substantial parallel processing, which is common in deep learning workloads.

Portability:
You get the flexibility to switch between devices. When you're on the go, you can still leverage the power of an eGPU setup when you're back at your workspace.

Compatibility:
macOS Mojave offers improved eGPU support, making it easier to integrate an external GPU without extensive configuration.

Recommended Nvidia eGPUs

Nvidia GeForce RTX 2060

Performance: GeForce RTX 2060 is a popular choice for deep learning enthusiasts due to its balance of performance and cost. It comes equipped with Ray Tracing Cores and Tensor Cores, specifically designed for machine learning tasks.

Compatibility: Ensure you have the latest Nvidia drivers compatible with macOS Mojave. The installation process is straightforward and integrates well with TensorFlow.

Nvidia Quadro P4000

Performance: This is a more professional-grade option. The Quadro P4000 has a higher VRAM and improved performance metrics, tailored for extensive computational tasks.

Compatibility: Similar to the RTX 2060 in driver compatibility, the Quadro P4000 also aligns well with macOS Mojave. This card is slightly pricier but offers better reliability and longevity.

Nvidia GTX 1080 Ti

Performance: The GTX 1080 Ti is another powerhouse, known for its high performance in gaming and computational tasks alike. With a large number of CUDA cores, it’s ideal for running sophisticated deep learning models.

Compatibility: This card has strong community support and extensive documentation, making it easier to work through any setup issues.

Conclusion

When it comes to selecting an Nvidia eGPU for your 2017 MacBook Pro running macOS Mojave, the GeForce RTX 2060, Quadro P4000, and GTX 1080 Ti are all excellent choices depending on your budget and performance needs. With any of these options, TensorFlow tasks will see a significant performance boost, transforming your MacBook Pro into a powerful tool for deep learning.

Investing in a reliable eGPU setup not only enhances your productivity but also assures you can tackle more complex models and larger datasets, thus propelling your deep learning projects to new heights.