Changelog

bixverse.gpu 0.3.1

Features

• Agent skill for using bixverse.gpu, shipped under inst/skills/ and installed with install_agent_skill_gpu(). Covers which GPU function replaces which bixverse step, what has no GPU path, and the traps. Same layout as bixverse::install_agent_skill(), with the API index generated by data-raw/generate_api_index.R.
• GPU-accelerated BBKNN.
• A GPU-accelerated implementation of NEBULA for lots and lots of cells.

bixverse.gpu 0.3.0

Features

• Take in substantial improvements on the Rust back-ends. The kNN searches now return Euclidean distances instead of squared Euclidean distances.

Deprecated

• The previous interface of generate_cagra_knn_sc(), find_neighbours_cagra_sc(), params_sc_cagra(), rs_cagra_gpu_knn(), rs_exhaustive_gpu_knn(), params_sc_ivf() has been deprecated. These are now all wired into generate_gpu_knn_sc().

bixverse.gpu 0.2.8

Features

• GPU-accelerated NMF for single cells and meta cells: nmf_gpu_sc(), stabilised_nmf_gpu_sc(), consensus_nmf_gpu_sc() and nmf_k_sweep_gpu_sc(), each dispatching on SingleCells and MetaCells.

bixverse.gpu 0.2.7

Features

• GPU-accelerated Scrublet via scrublet_gpu_sc(). The randomised sparse SVD, the projection of the simulated doublets and the kNN over the combined embedding run on GPU. Full parity with bixverse::scrublet_sc(), group_by included, and the same ScrubletRes object comes back.
• params_scrublet_gpu() picks between the GPU and the CPU nearest neighbour indices through knn_backend, with the knn block validated against whichever one was asked for. params_knn_gpu_defaults() holds the GPU-side defaults.
• Improvements in terms of kernels taken from ann-search-rs.

bixverse.gpu 0.2.6

Features

• GPU-accelerated fast clustering for single cell.

bixverse.gpu 0.2.5

Features

• GPU-accelerated SEACells: both Frank-Wolfe solves, the B-gradient argmin and the per-cell A columns, are executed on GPU, increasing the speed on larger data sets.
• Version bumps to get improved GPU performance for the UMAP optimiser from manifolds-rs.

bixverse.gpu 0.2.4

Features

• Update to bixverse-rs to enable the new streaming engine.

bixverse.gpu 0.2.3

Fix

• Potentially broken manifoldsR dependency.

bixverse.gpu 0.2.2

Features

• GPU-accelerated SCENIC
• Improvement in the GPU-accelerated kNN searches ported over from ann-search-rs.
• Handrolled correlation kernels to increase performance there.

bixverse.gpu 0.2.1

Features

• GPU-accelerated UMAP optimisation exposed.
• GPU-accelerated kNN generation for both tSNE and UMAP (longer term also a GPU-accelerated tSNE optimiser planned). Additionally, the kNN graphs can be used more broadly.
• umap_gpu_sc() and tsne_gpu_sc() wire the GPU UMAP and t-SNE paths directly into the SingleCells workflow, mirroring bixverse::umap_sc() and bixverse::tsne_sc().

bixverse.gpu 0.2.0

Major release.

Features

• CPU-backend of parametric UMAP changed to flex from burn for better speed. Reduces also dependencies and packages and easier installation on Linux.
• GPU-accelerated methods for single cell:
  • kNN graphs are now multi-modal (see bixverse version "0.4.0")
  • sparse, randomised SVD on GPU available
  • GPU-accelerated Harmony (version 2).
• New GPU-accelerated methods:
  • k-means clustering
  • Correlations and co-variances supported on GPU.
• Option addded to save parametric UMAP models

bixverse.gpu 0.1.3

Features

• Port to rextendr 0.5.0 and updated Rust <> R APIs and various version updates.

bixverse.gpu 0.1.2

Features

• Version bumps on different Rust crates.

bixverse.gpu 0.1.1

Features

• Parametric UMAP added; leverages a small neural net that can be trained and then used subsequently for repeat predictions.

bixverse.gpu 0.1.0

Features

• Package release with GPU-accelerated kNN searches implemented for SingleCells.