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The Slurm Workload Administrator (previously known as easy Linux Energy for Reference Management or SLURM), or Slurm, is a free of charge and open-source job scheduler for Linux and Unix-like kernels, employed by lots of the world’s supercomputers and computer clusters. It offers three key functions. First, it allocates exclusive and/or non-exclusive usage of resources (computer nodes) to users for a few passage of time to allow them to perform work. Second, it offers a platform for starting, performing, and monitoring work (typically a parallel job such as MPI) on a couple of allocated nodes. Finally, it arbitrates contention for resources by owning a queue of pending careers. Slurm is the workload administrator on about 60% of the TOP500 supercomputers, including Tianhe-2 that, until 2016, was the world’s speediest computer.Slurm runs on the best fit algorithm predicated on Hilbert curve arranging or extra fat tree network topology to be able to optimize area of task projects on parallel computer systems.

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In cognitive psychology, cognitive load refers to the effort being used in the working memory. Cognitive load theory was developed out of the study of problem solving by John Sweller in the late 1980s. Sweller argued that instructional design can be used to reduce cognitive load in learners. Cognitive load theory differentiates cognitive load into three types: intrinsic, extraneous, and germane. Intrinsic cognitive load is the effort associated with a specific topic. Extraneous cognitive load refers to the way information or tasks are presented to a learner. And, germane cognitive load refers to the work put into creating a permanent store of knowledge, or a schema. Researchers Paas and Van Merriënboer developed a way to measure perceived mental effort which is indicative of cognitive load. Task-invoked pupillary response is a reliable and sensitive measurement of cognitive load that is directly related to working memory. Measuring humans’ pupil responses has the potential to improve human–computer interaction and adaptive decision support systems. Heavy cognitive load can have negative effects on task completion, and it is important to note that the experience of cognitive load is not the same in everyone. The elderly, students, and children experience different, and more often higher, amounts of cognitive load. High cognitive load in the elderly has been shown to affect their center of balance. With increased distractions and cell phone use students are more prone to experiencing high cognitive load which can reduce academic success. Children have less general knowledge than adults which increases their cognitive load. Recent theoretical advances include the incorporation of embodied cognition in order to predict the cognitive load resulting from embodied interactions.

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