Effective kernel mapping for OpenCL applications in heterogeneous platforms
Author
Albayrak, Ömer Erdil
Aktürk, İsmail
Öztürk, Özcan
Date
2012-09Source Title
International Conference on Parallel Programming
Print ISSN
1530-2016
Publisher
Institute of Electrical and Electronics Engineers
Pages
81 - 88
Language
English
Type
Conference PaperItem Usage Stats
143
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163
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Abstract
Many core accelerators are being deployed in many systems to improve the processing capabilities. In such systems, application mapping need to be enhanced to maximize the utilization of the underlying architecture. Especially in GPUs mapping becomes critical for multi-kernel applications as kernels may exhibit different characteristics. While some of the kernels run faster on GPU, others may refer to stay in CPU due to the high data transfer overhead. Thus, heterogeneous execution may yield to improved performance compared to executing the application only on CPU or only on GPU. In this paper, we propose a novel profiling-based kernel mapping algorithm to assign each kernel of an application to the proper device to improve the overall performance of an application. We use profiling information of kernels on different devices and generate a map that identifies which kernel should run on where to improve the overall performance of an application. Initial experiments show that our approach can effectively map kernels on CPU and GPU, and outperforms to a CPU-only and GPU-only approach. © 2012 IEEE.
Keywords
GPUHeterogeneous
Kernel
Mapping
OpenCL
Application mapping
GPU
Heterogeneous platforms
Kernel mapping
Many core
Multi-kernel
Processing capability
Conformal mapping
Data transfer
Program processors
Embedded systems