Zahereel Ishwar Abdul Khalib
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Preferred name
Zahereel Ishwar Abdul Khalib
Official Name
Zahereel Ishwar, Abdul Khalib
Alternative Name
Khalib, Zahereel
Khalib, Z. I.Abdul
Khalib, Z. I.A.
Khalib, Zia • Khalib
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Scopus Author ID
24824279500
Researcher ID
CYK-9763-2022

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  • Publication
    Gaining Speedup with OpenMP Schedule Type under Imbalance Workload
    ( 2023-10-06)
    Zahereel Ishwar Abdul Khalib
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Qun N.H.
    ;
    Rahman M.
    ;
    Hossen M.A.
    Despite OpenMP being the defacto standard for parallel programming on shared memory system, little is known on how its schedule type and chunk size effect the parallel performance of shared memory multicore processor. Performance analysis in the literature have overlooked the effects of different schedule type and chunk size, possibly it was simply not the focus of their research. Often, the researchers did not specify the schedule type explicitly. This has resulted in the default way of assigning the loop iterations among threads. By default, the static schedule is used and the size of chunk which is the ratio of total number of iterations to the number of threads is implemented. Contrary to above, this research proposes a guideline to select the appropriate schedule type and chunk size for achieving optimum performance on different shared memory multicore platform for balanced and imbalance workload. Three multicore technology namely Intel Core i5-2410M, AMD A12-9700P and ARM Cortex-A53 are used for this work. The speedup obtained after turning on/off certain multicore technologies and a selected number of active cores per processor is analyzed. The result of analysis enables the user to justify and exercise trade-offs in selecting OpenMP schedule type and chunk size, and also in choosing the multicore technologies to meet the desired performance gain. Results analyzed over various configurations of multicore platform and workload suggested that under certain constraint different schedule types and chunk sizes have led to better speedup.
      1
  • Publication
    Ant colony algorithm to generate t-way test suite with constraints
    ( 2020-06-17)
    Nuraminah Ramli
    ;
    Rozmie Razif Othman
    ;
    Zahereel Ishwar Abdul Khalib
    ;
    Zahereel Ishwar Abdul Khalib
    ;
    Fauzi S.S.M.
    T-way testing is one of the testing techniques offered to generate test suites. It focuses on interactions of input parameters based on strength. Besides that, t-way is used to overcome exhaustive testing problem. Another important aspect in t-way is constraints. It forbids certain interactions of input parameters. Therefore, the final test suite contains only valid interactions. T-way testing is NP-hard problem. No single strategy can always generates the best test suite size at all time for all configurations. Thus, Const-TTSGA strategy has been developed to generate test suites. The strategy supports constraints variable strength. Const-TTSGA is a metaheuristic strategy which applies ant colony algorithm to generate the best test cases. Two types of experiments have been conducted; constraints uniform and variable strength which consists of few other configurations. Results obtained are compared to benchmarked results. Const-TTSGA outperformed other strategy for costraints uniform strength experiments except for one configuration. However, the strategy outperformed other strategies for constraints variable strength experiments.
      1