Optimization of kernel learning algorithm based on parallel architecture

Li, Lü; Chen, Xin

doi:10.1007/s00607-019-00760-1

Cited by 1 publication

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Matrix inversion, recognized as a fundamental yet computationally intensive mathematical problem, often constitutes the most time-intensive portion of numerous computational tasks. [1][2][3] In practical engineering, matrix inversion modules serve as fundamental components for an extensive array of problems, such as machine learning [4][5][6] and signal processing. 7,8 The time complexity of matrix inversion on traditional computing systems typically scales as ∼O(N 2.37 ) even with the most advanced algorithms.…”

Section: Introductionmentioning

confidence: 99%

Chip-scale all-optical complex-valued matrix inverter

Liu,

Cheng,

Zhou

et al. 2024

APL Photonics

View full text Add to dashboard Cite

Matrix inversion is a fundamental and widely utilized linear algebraic operation but computationally expensive in digital-clock-based platforms. Optical computing is a new computing paradigm with high speed and energy efficiency, and the computation can be realized through light propagation. However, there is a scarcity of experimentally implemented matrix inverters that exhibit both high integration density and the capability to perform complex-valued operations in existing optical systems. For the first time, we experimentally demonstrated an iterative all-optical chip-scale processor to perform the computation of complex-valued matrix inversion using the Richardson method. Our chip-scale processor achieves an iteration speed of 10 GHz, which can facilitate ultra-fast matrix inversion with the assistance of high-speed Mach–Zehnder interferometer modulators. The convergence can be attained within 20 iterations, yielding an accuracy of 90%. The proposed chip-scale all-optical complex-valued matrix inverter represents a distinctive innovation in the field of all-optical recursive systems, offering significant potential for solving computationally intensive mathematical problems.

show abstract