Paper Info
Title
OPTiC: Optimizing Collaborative CPU–GPU Computing on Mobile Devices With Thermal Constraints
Abstract
The CPU-graphic processing unit (GPU) co-execution of computation kernels on heterogeneous multiprocessor system-on-chip can significantly boost performance compared to the execution on either the CPU or the GPU alone. However, engaging multiple on-chip compute elements concurrently at the highest frequency may not provide the optimal performance in a mobile system with stringent thermal constraints. The system may repeatedly exceed the temperature threshold necessitating frequency throttling and hence performance degradation. We present OPTiC, an analytical framework that given a computation kernel can automatically select the partitioning point and the operating frequencies for optimal CPU–GPU co-execution under thermal constraints. OPTiC estimates, through modeling, CPU and GPU power, performance at different frequency points as well as the performance impact of thermal throttling and memory contention. Experimental evaluation on a commercial mobile platform shows that OPTiC achieves an average 13.68% performance improvement over existing schemes that enable co-execution without thermal considerations.
Year
DOI
Venue
2019
10.1109/TCAD.2018.2873210
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Keywords
Field
DocType
Graphics processing units,Runtime,Central Processing Unit,Kernel,Computer architecture,Temperature sensors,Performance evaluation
Kernel (linear algebra),Central processing unit,Computer science,Parallel computing,Multiprocessing,Real-time computing,Mobile device,General-purpose computing on graphics processing units,Bandwidth throttling,Performance improvement,Computation
Journal
Volume
Issue
ISSN
38
3
0278-0070
Citations 
PageRank 
References 
1
0.37
0
Authors
3
Name
Order
Citations
PageRank
Siqi Wang1375.39
Gayathri Ananthanarayanan221.07
Tulika Mitra32714135.99