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TamaRISC-CS: An Ultra-Low-Power Application-Specific Processor for Compressed Sensing

Constantin, Jeremy; Dogan, Ahmed; Andersson, Oskar LU ; Meinerzhagen, Pascal; Rodrigues, Joachim LU ; Atienza, David and Burg, Andreas (2012) IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SOC) In IEEE/IFIP 20th International Conference on VLSI and System-on-Chip (VLSI-SoC), 2012 p.159-164
Abstract
Compressed sensing (CS) is a universal technique for the compression of sparse signals. CS has been widely used in sensing platforms where portable, autonomous devices have to operate for long periods of time with limited energy resources. Therefore, an ultra-low-power (ULP) CS implementation is vital for these kind of energy-limited systems. Sub-threshold (sub-VT) operation is commonly used for ULP computing, and can also be combined with CS. However, most established CS implementations can achieve either no or very limited benefit from sub-VT operation. Therefore, we propose a sub-VT application-specific instruction-set processor (ASIP), exploiting the specific operations of CS. Our results show that the proposed ASIP accomplishes 62x... (More)
Compressed sensing (CS) is a universal technique for the compression of sparse signals. CS has been widely used in sensing platforms where portable, autonomous devices have to operate for long periods of time with limited energy resources. Therefore, an ultra-low-power (ULP) CS implementation is vital for these kind of energy-limited systems. Sub-threshold (sub-VT) operation is commonly used for ULP computing, and can also be combined with CS. However, most established CS implementations can achieve either no or very limited benefit from sub-VT operation. Therefore, we propose a sub-VT application-specific instruction-set processor (ASIP), exploiting the specific operations of CS. Our results show that the proposed ASIP accomplishes 62x speed-up and 11.6x power savings with respect to an established CS implementation running on the baseline low-power processor. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
IEEE/IFIP 20th International Conference on VLSI and System-on-Chip (VLSI-SoC), 2012
pages
159 - 164
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SOC)
external identifiers
  • Scopus:84872183309
ISBN
978-1-4673-2657-5
DOI
10.1109/VLSI-SoC.2012.6379023
language
English
LU publication?
yes
id
c4f2cb6a-dea3-4cce-becd-7c9c260ecbcf (old id 2968408)
date added to LUP
2012-08-09 13:06:31
date last changed
2016-10-13 04:51:20
@misc{c4f2cb6a-dea3-4cce-becd-7c9c260ecbcf,
  abstract     = {Compressed sensing (CS) is a universal technique for the compression of sparse signals. CS has been widely used in sensing platforms where portable, autonomous devices have to operate for long periods of time with limited energy resources. Therefore, an ultra-low-power (ULP) CS implementation is vital for these kind of energy-limited systems. Sub-threshold (sub-VT) operation is commonly used for ULP computing, and can also be combined with CS. However, most established CS implementations can achieve either no or very limited benefit from sub-VT operation. Therefore, we propose a sub-VT application-specific instruction-set processor (ASIP), exploiting the specific operations of CS. Our results show that the proposed ASIP accomplishes 62x speed-up and 11.6x power savings with respect to an established CS implementation running on the baseline low-power processor.},
  author       = {Constantin, Jeremy and Dogan, Ahmed and Andersson, Oskar and Meinerzhagen, Pascal and Rodrigues, Joachim and Atienza, David and Burg, Andreas},
  isbn         = {978-1-4673-2657-5},
  language     = {eng},
  pages        = {159--164},
  publisher    = {ARRAY(0x8e18210)},
  series       = {IEEE/IFIP 20th International Conference on VLSI and System-on-Chip (VLSI-SoC), 2012},
  title        = {TamaRISC-CS: An Ultra-Low-Power Application-Specific Processor for Compressed Sensing},
  url          = {http://dx.doi.org/10.1109/VLSI-SoC.2012.6379023},
  year         = {2012},
}