<p dir="auto">I've been trying to implement Gaussian Processes Regression, which require the calculation of a matrix inverse. With regular numpy I would use <code class="notranslate">np.linalg.inv</code>, but I can't find this function back in jax.</p>
<p dir="auto">Everything else is working as expected, and I can use <code class="notranslate">np.linalg.inv</code> for basic calculations.<br>
Unfortunately, the use of <code class="notranslate">np.linalg.inv</code> keeps me from using <code class="notranslate">grad</code> to calculate gradients, which would be the most exciting part of the whole implementation!</p>
<p dir="auto">I would love to contribute a PR if someone can tell me where to start.</p>
<p dir="auto">With multiple GPUs there should be a way to direct specific computations to run on a specific GPU.</p>
<p dir="auto">Context: I want to run #gpu different models in parallel each on its own GPU.</p>
<p dir="auto">The current best solution that comes to mind is to RPC between different machines, each with 1 GPU -- I'd like to avoid doing this.</p>
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