FPGA implementation of Hardware Accelerated 64-bit Floating Point Matrix-Multiplier for GNSS Data Processing

This paper presents FPGA-based implementation of hardware accelerated matrix multiplier using High Level Synthesis (HLS) technique with a specific linkage to GNSS data processing. Matrix multiplication operation is a vital block for GNSS data processing. The multiplication of matrices of order greater than 10 consumes significant time in FPGA-based design. The total time for data processing need to be reduced for real-time scenario specially in case of space-based GNSS applications. For this purpose, HLS IP for matrix multiplication is developed to reduce the processing time substantially. In this work, 64-bit floating point data processing is achieved on 32–bit softcore processor, by design of control logic for seamless dataflow and synchronization between the HLS IP and other key modules in the FPGA. The design is tested in Xilinx Kintex Ultra FPGA-based KCU105 evaluation board. The hardware result for 40x40 matrices show that HLS-based approach achieves speedup factor up to 286 over standalone MicroBlaze softcore processor, this speedup is achieved at the expense of less than 3% percent of available major resources in the FPGA.

Authors

Institutions

Publication Details

Published
2025-02-27
DOI
https://doi.org/10.1109/isacc65211.2025.10969225
Citations
1
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
4.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

FPGA implementation of Hardware Accelerated 64-bit Floating Point Matrix-Multiplier for GNSS Data Processing

Nilay Jadav, Durga Digdarsini, Hem Raj Shau, Guru Vignesh G
1 citations
Inertial Sensor and Navigation
4.99
article

FPGA implementation of Hardware Accelerated 64-bit Floating Point Matrix-Multiplier for GNSS Data Processing

Nilay Jadav, Durga Digdarsini, Hem Raj Shau, Guru Vignesh G
article en
1 citations

Abstract

This paper presents FPGA-based implementation of hardware accelerated matrix multiplier using High Level Synthesis (HLS) technique with a specific linkage to GNSS data processing. Matrix multiplication operation is a vital block for GNSS data processing. The multiplication of matrices of order greater than 10 consumes significant time in FPGA-based design. The total time for data processing need to be reduced for real-time scenario specially in case of space-based GNSS applications. For this purpose, HLS IP for matrix multiplication is developed to reduce the processing time substantially. In this work, 64-bit floating point data processing is achieved on 32–bit softcore processor, by design of control logic for seamless dataflow and synchronization between the HLS IP and other key modules in the FPGA. The design is tested in Xilinx Kintex Ultra FPGA-based KCU105 evaluation board. The hardware result for 40x40 matrices show that HLS-based approach achieves speedup factor up to 286 over standalone MicroBlaze softcore processor, this speedup is achieved at the expense of less than 3% percent of available major resources in the FPGA.

Indian Space Research Organisation (IN), Charotar University of Science and Technology (IN), PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN)
Affordable and clean energy
Openalex Percentile: Top 6%
Inertial Sensor and Navigation
4.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.