Dataflow Systolic Array Implementations of Exploring Dual-Triangular Structure in QR Decomposition Using High-Level Synthesis

Siyang Jiang, Hsi-Wen Chen, Ming-Syan Chen

Abstract: Tall and skinny QR (TSQR) decomposition is an essential matrix operation with various applications in edge computing, including data compression, subspace projection, and dimension reduction. As a critical component in TSQR, Dual-Triangular QR (DTQR) decomposition is solved by the Normal QR method in most works without utilizing the dual-triangular structure. Therefore, we propose a novel DTQR accelerator by recursively exploring the DT structure and propose three acceleration strategies with the systolic array to achieve higher parallelism. Experimental results manifest that our algorithm achieves 21.55x on average speedup compared with the baselines.