NDLI: A Low-Power Heterogeneous Multiprocessor Architecture for Audio Signal Processing

Content Provider	Springer Nature Link
Author	Paker, Özgün Sparsø, Jens Haandbæk, Niels Isager, Mogens Nielsen, Lars Skovby
Copyright Year	2004
Abstract	This paper describes a low-power programmable DSP architecture that targets audio signal processing. The architecture can be characterized as a heterogeneous multiprocessor consisting of small instruction set processors called mini-cores as well as standard DSP and CPU cores that communicate using message passing. The mini-cores are tailored for different classes of filtering algorithms (FIR, IIR, N-LMS etc.), and in a typical system the communication among processors occur at the sampling rate only.The mini-cores are intended as soft-macros to be used in the implementation of system-on-chip solutions using a synthesis-based design flow targeting a standard-cell implementation. They are parameterized in word-size, memory-size, etc. and can be instantiated according to the needs of the application. To give an impression of the size of a mini-core we mention that one of the FIR mini-cores in a prototype design has 16 instructions, a 32-word × 16-bit program memory, a 64-word × 16-bit data memory and a 25-word × 16-bit coefficient memory.Results obtained from the design of a prototype chip containing mini-cores for a hearing aid application, demonstrate a power consumption that is only 1.5–1.6 times larger than a hardwired ASIC and more than 6–21 times lower than current state of the art low-power DSP processors. This is due to: (1) the small size of the processors and (2) a smaller instruction count for a given task.
Starting Page	95
Ending Page	110
Page Count	16
File Format	PDF
ISSN	09225773
Journal	Journal of Signal Processing Systems
Volume Number	37
Issue Number	1
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2004-05-01
Publisher Place	Boston
Access Restriction	Subscribed
Subject Keyword	Signal, Image and Speech Processing Circuits and Systems Electrical Engineering Image Processing and Computer Vision Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Information Systems Electrical and Electronic Engineering

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