Title
Power optimization in heterogenous datapaths.
Abstract
Heterogenous datapaths maximize the utilization of functional units (FUs) by customizing their widths individually through fragmentation of wide operands. In comparison, slices in large functional units in a homogenous datapath could be spending many cycles not performing actual useful work. Various fragmentation techniques demonstrated benefits in minimizing the total functional unit area. Upon a closer look at fragmentation techniques, we observe that the area savings achieved by heterogenous datapaths can be traded-off for power optimization. Our specific approach is to introduce choices for functional units with power/area trade-offs for different fragmentation and allocation choices, for reducing power consumption while satisfying the area constraint imposed on the heterogenous datapath. As low power FUs in literature produce an area penalty, a methodology must be developed in order to introduce them in the HLS flow while complying with the area constraint. We propose an allocation and module selection algorithms that pursue a trade-off between area and power consumption for fragmented datapaths under a total area constraint. Results show that it is possible to reduce power by 37% on average (49% in the best case). Moreover latency and cycle time will be equal or nearly the same as in the baseline case, which will lead to an energy reduction, too.
Year
DOI
Venue
2011
10.1109/DATE.2011.5763226
DATE
Keywords
Field
DocType
high level synthesis,cycle time,switches,area,discrete cosine transform,satisfiability,resource management,resource manager,functional unit,optimization,power optimization,adders,scheduling
Datapath,Power optimization,Adder,Latency (engineering),Computer science,Scheduling (computing),High-level synthesis,Operand,Parallel computing,Fragmentation (computing),Real-time computing
Conference
ISSN
ISBN
Citations 
1530-1591
978-1-61284-208-0
0
PageRank 
References 
Authors
0.34
10
5
Name
Order
Citations
PageRank
Alberto A. Del Barrio17814.49
Seda Öǧrenci Memik248842.57
María C. Molina3776.97
José M. Mendías427319.60
Román Hermida58915.34