CORAL: Verification-Aware OpenCL Based Read Mapper for Heterogeneous Systems

Maheshwari, Sidharth and Acharyya, A. and et al, . (2021) CORAL: Verification-Aware OpenCL Based Read Mapper for Heterogeneous Systems. IEEE/ACM Trans. Comput. Biol. and Bioinf., 18 (4). pp. 1426-1438. ISSN 15455963

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Genomics has the potential to transform medicine from reactive to a personalized, predictive, preventive, and participatory (P4) form. Being a Big Data application with continuously increasing rate of data production, the computational costs of genomics have become a daunting challenge. Most modern computing systems are heterogeneous consisting of various combinations of computing resources, such as CPUs, GPUs, and FPGAs. They require platform-specific software and languages to program making their simultaneous operation challenging. Existing read mappers and analysis tools in the whole genome sequencing (WGS) pipeline do not scale for such heterogeneity. Additionally, the computational cost of mapping reads is high due to expensive dynamic programming based verification, where optimized implementations are already available. Thus, improvement in filtration techniques is needed to reduce verification overhead. To address the aforementioned limitations with regards to the mapping element of the WGS pipeline, we propose a Cross-platfOrm Read mApper using opencL (CORAL). CORAL is capable of executing on heterogeneous devices/platforms, simultaneously. It can reduce computational time by suitably distributing the workload without any additional programming effort. We showcase this on a quadcore Intel CPU along with two Nvidia GTX 590 GPUs, distributing the workload judiciously to achieve up to 2× speedup compared to when, only, the CPUs are used. To reduce the verification overhead, CORAL dynamically adapts k-mer length during filtration. We demonstrate competitive timings in comparison with other mappers using real and simulated reads. CORAL is available at:

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IITH Creators:
IITH CreatorsORCiD
Acharyya, Amit
Item Type: Article
Uncontrolled Keywords: Big data applications, Computational costs, Filtration techniques, Heterogeneous devices, Heterogeneous systems, Optimized implementation, Simultaneous operation, Whole genome sequencing
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: Mrs Haseena VKKM
Date Deposited: 23 Nov 2021 07:06
Last Modified: 04 Mar 2022 07:14
Publisher URL:
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