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We present qrpca, a fast and scalable QR-decomposition principal componentanalysis package. The software, written in both R and python languages, makesuse of torch for internal matrix computations, and enables GPU acceleration,when available. qrpca provides similar functionalities to prcomp (R) andsklearn (python) packages respectively. A benchmark test shows that qrpca canachieve computational speeds 10-20 $\times$ faster for large dimensionalmatrices than default implementations, and is at least twice as fast for astandard decomposition of spectral data cubes. The qrpca source code is madefreely available to the community.

qrpca: A Package for Fast Principal Component Analysis with GPU Acceleration