Dataflow Systolic Array Implementations of Exploring Dual-Triangular Structure in QR Decomposition Using High-Level Synthesis
Journal
2021 International Conference on Field-Programmable Technology, ICFPT 2021
Date Issued
2021
Author(s)
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. ? 2021 IEEE.
Subjects
Dual-triangular matrix
High-Level Synthesis
QR decomposition
High level synthesis
Matrix algebra
Dataflow
Edge computing
Essential matrix
High-level synthesis
Matrix operations
Subspace projection
Triangular matrix
Triangular structures
Systolic arrays
Other Subjects
High level synthesis; Matrix algebra; Dataflow; Dual-triangular matrix; Edge computing; Essential matrix; High-level synthesis; Matrix operations; QR decomposition; Subspace projection; Triangular matrix; Triangular structures; Systolic arrays
Type
conference paper