Multi CPU / GPU capabilities?

@lmcinnes
As you may have guessed I have several CPUs and GPUs at hand and I work with high-dimensional data.
Now I am benching a 500k * 5k => 500k * 2 vector vs. PCA (I need a high level clustering to filter my data to feed it further in the pipeline).

So a couple of questions:
1. Any plans on multi-CPU / GPU support?
2. Does your implementation utilize vectorized operations (not really sure how embedding methods like T-SNE and UMAP work, I believe they minimize some kind of distance in high dimension space?) If so, can I help?
3. Did you run benchmarks (like HDBSCAN) on large and huge datasets? If so, then is it feasible to expect 500k * 5k => 500k * 2 to finish in reasonable time, or should I do PCA => UMAP?

The issue names no files, tests, or entry points. Start by locating the UMAP implementation and any existing benchmark coverage, then investigate the requested multi-CPU/GPU support, vectorization, and 500k × 5k workload; done would require a clearly scoped change or maintainer-backed benchmark conclusion.

Written by the indexing model from the issue text.