74,512 research outputs found

    Load-Sharing Policies in Parallel Simulation of Agent-Based Demographic Models

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    Execution parallelism in agent-Based Simulation (ABS) allows to deal with complex/large-scale models. This raises the need for runtime environments able to fully exploit hardware parallelism, while jointly offering ABS-suited programming abstractions. In this paper, we target last-generation Parallel Discrete Event Simulation (PDES) platforms for multicore systems. We discuss a programming model to support both implicit (in-place access) and explicit (message passing) interactions across concurrent Logical Processes (LPs). We discuss different load-sharing policies combining event rate and implicit/explicit LPs’ interactions. We present a performance study conducted on a synthetic test case, representative of a class of agent-based models

    Load-sharing policies in parallel simulation of agent-based demographic models

    Get PDF
    Execution parallelism in agent-Based Simulation (ABS) allows to deal with complex/large-scale models. This raises the need for runtime environments able to fully exploit hardware parallelism, while jointly offering ABS-suited programming abstractions. In this paper, we target last-generation Parallel Discrete Event Simulation (PDES) platforms for multicore systems. We discuss a programming model to support both implicit (in-place access) and explicit (message passing) interactions across concurrent Logical Processes (LPs). We discuss different load-sharing policies combining event rate and implicit/explicit LPs’ interactions. We present a performance study conducted on a synthetic test case, representative of a class of agent-based models.Peer ReviewedPostprint (author's final draft

    An efficient MPI/OpenMP parallelization of the Hartree-Fock method for the second generation of Intel Xeon Phi processor

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    Modern OpenMP threading techniques are used to convert the MPI-only Hartree-Fock code in the GAMESS program to a hybrid MPI/OpenMP algorithm. Two separate implementations that differ by the sharing or replication of key data structures among threads are considered, density and Fock matrices. All implementations are benchmarked on a super-computer of 3,000 Intel Xeon Phi processors. With 64 cores per processor, scaling numbers are reported on up to 192,000 cores. The hybrid MPI/OpenMP implementation reduces the memory footprint by approximately 200 times compared to the legacy code. The MPI/OpenMP code was shown to run up to six times faster than the original for a range of molecular system sizes.Comment: SC17 conference paper, 12 pages, 7 figure

    Improving skills in rounding off the whole number

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    This study was conducted to address teaching and learning skills in rounding off a whole number. This study consisted of 15 years 4 students from the Kong Nan Chinese Primary School, Parit Raja, Johor, Malaysia. Initial survey to identify this problem was carried out by analyzing the exercise books and exercises in pre-test. Based on these analyses, a large number of students were not proficient in relevant skills. A ‘q’ technique was introduced as an approach in teaching and learning to help students master the skills of rounding whole numbers. In summary, this technique helps students to remember the sequence of processes and process in rounding numbers. A total of four sessions of teaching and learning activities that take less than an hour have been implemented specifically to help students to master this technique. Results of the implementation of these activities have shown very positive results among the students. Two post tests were carried out to see the effectiveness of techniques and the results shows that 100% of students were able to answer correctly at least three questions correctly. The t-test analysis was clearly showed the effectiveness of ‘q’ technique. This technique also indirectly helps to maintain and increase student interest in learning Mathematics. This is shown with the active involvement of students in answering questions given by the teacher
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