Understanding Parallel Computing: GPUs vs CPUs Explained Simply with role of CUDA
In this article we will understand the role of CUDA, and how GPU and CPU play distinct roles, to enhance performance and efficiency.
In this article we will understand the role of CUDA, and how GPU and CPU play distinct roles, to enhance performance and efficiency.
In this article, we look at and compare the A100 with the powerful, new Nvidia GPU, the Hopper H100.
In this review, we look at how different medical techniques for drug discovery are enabled by Nvidia GPUs like those offered on Paperspace.
How to run Nvidia H100 single and 8x multi-GPU machines on Paperspace.
In the Kaggle vs. Paperspace debate, the choice ultimately depends on individual needs and preferences. In this article we aim to help users make a smart choice between the two platforms.
In this blog post, we compare and contrast the capabilities of Google Colab and Paperspace Notebooks, and demonstrate the differences in efficacy of each for implementing inference with an AI model.
In this article, we walk through the steps for running MLPerf 3.0 on Paperspace GPUs in order to show how we achieve peak performances for AI training, comparable to Nvidia's own reported results.
In this blogpost we take a look at the three best GPU rendering softwares: Redshift, Octane, and Vray, and compare their functionalities for users to keep in mind when choosing their tools on Paperspace Core
In this tutorial, we examine mixed-precision training to try and understand how we can leverage it in our code, how it fits into the traditional DL algorithmic paradigm, what frameworks support mixed precision training, and performance tips on using GPUs for DL with automatic mixed precision.