DocumentCode :
1997469
Title :
OpenCL Performance Evaluation on Modern Multi Core CPUs
Author :
Joo Hwan Lee ; Patel, K. ; Nigania, Nimit ; Hyojong Kim ; Hyesoon Kim
Author_Institution :
Sch. of Comput. Sci., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2013
fDate :
20-24 May 2013
Firstpage :
1177
Lastpage :
1185
Abstract :
Utilizing heterogeneous platforms for computation has become a general trend making the portability issue important. OpenCL (Open Computing Language) serves the purpose by enabling portable execution on heterogeneous architectures. However, unpredictable performance variation on different platforms has become a burden for programmers who write OpenCL programs. This is especially true for conventional multicore CPUs, since the performance of general OpenCL applications on CPUs lags behind the performance expected by the programmer considering the conventional parallel programming model. In this paper, we evaluate the performance of OpenCL programs on out-of-order multicore CPUs from the architectural perspective. We evaluate OpenCL programs on various aspects, including scheduling overhead, instruction-level parallelism, address space, data location, locality, and vectorization, comparing OpenCL to conventional parallel programming models for CPUs. Our evaluation indicates different performance characteristic of OpenCL programs and also provides insight into the optimization metrics for better performance on CPUs.
Keywords :
microprocessor chips; multiprocessing systems; optimisation; parallel architectures; parallel programming; performance evaluation; processor scheduling; OpenCL performance evaluation; address space; data location; heterogeneous architectures; instruction-level parallelism; open computing language; optimization metrics; out-of-order multicore CPU; parallel programming model; portability issue; scheduling overhead; Benchmark testing; Kernel; Multicore processing; Performance evaluation; Program processors; Programming; Data Transfer; ILP; Locality; OpenCL Performance on CPU; Scheduling Overhead; Vectorization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2013 IEEE 27th International
Conference_Location :
Cambridge, MA
Print_ISBN :
978-0-7695-4979-8
Type :
conf
DOI :
10.1109/IPDPSW.2013.141
Filename :
6651004
Link To Document :
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