Paper Info
Title
Synchronizing code execution on ultra-low-power embedded multi-channel signal analysis platforms
Abstract
Embedded biosignal analysis involves a considerable amount of parallel computations, which can be exploited by employing low-voltage and ultra-low-power (ULP) parallel computing architectures. By allowing data and instruction broadcasting, single instruction multiple data (SIMD) processing paradigm enables considerable power savings and application speedup, in turn allowing for a lower voltage supply for a given workload. The state-of-the-art multi-core architectures for biosignal analysis however lack a bare, yet smart, synchronization technique among the cores, allowing lockstep execution of algorithm parts that can be performed using the SIMD, even in the presence of data-dependent execution flows. In this paper, we propose a lightweight synchronization technique to enhance an ULP multi-core processor, resulting in improved energy efficiency through lockstep SIMD execution. Our results show that the proposed improvements accomplish tangible power savings, up to 64% for an 8-core system operating at a workload of 89 MOps/s while exploiting voltage scaling.
Year
DOI
Venue
2013
10.7873/DATE.2013.090
DATE
Keywords
Field
DocType
single instruction multiple data,hardware,synchronization,data level parallelism,simd,parallel computing,multicore processing,network on chip,benchmark testing
Synchronization,Computer science,Lockstep,Synchronizing,Parallel computing,SIMD,Network on a chip,Real-time computing,Data parallelism,Biosignal,Speedup,Embedded system
Conference
ISSN
Citations 
PageRank 
1530-1591
1
0.38
References 
Authors
6
6
Name
Order
Citations
PageRank
Ahmed Yasir Dogan1292.75
Ruben Braojos2234.04
Jeremy Constantin3404.86
Giovanni Ansaloni49815.78
A. Burg51426126.54
David Atienza62219149.60