A Comparative Study of Programming Environments Exploiting Heterogeneous Systemsopen access
- Authors
- Ko, Bongsuk; Han, Seunghun; Park, Yongjun; Jeon, Moongu; Lee, Byeongcheol
- Issue Date
- May-2017
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Big data processing; heterogeneous systems; programming environment
- Citation
- IEEE ACCESS, v.5, pp.10081 - 10092
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE ACCESS
- Volume
- 5
- Start Page
- 10081
- End Page
- 10092
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/152418
- DOI
- 10.1109/ACCESS.2017.2708738
- ISSN
- 2169-3536
- Abstract
- This paper compares programming environments that exploit heterogeneous systems to process a large amount of data efficiently. Our motivation is to investigate the feasibility of the adaptive, transparent migration of intensive computation for a large amount of data across heterogeneous programming languages and processors for high performance and programmability. We compare a variety of programming environments composed of programming languages, such as Java and C, memory space models, such as distinct and shared memory, and parallel processors, such as general-purpose CPUs and graphics processing units (GPUs) to examine their performance-programmability tradeoffs. In addition, we introduce a software based shared virtual memory that creates a view of the host memory inside GPU kernels to enable seamless computation offloading from the host to the device. This paper reveals a programmability-performance hierarchy in which programs increase their performance at the cost of decreasing programmability. The experimental results suggest the desirability of a well-balanced system.
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