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Lecture 1A - HPC Cluster Organization
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<time class="meta__text" datetime="2020-11-05T00:00:00">November 05, 2020</time>
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<h3>HPC, HTC and Cloud</h3>
<p>HPC, HTC, and Cloud Computing are modern answers to “too much data”.</p>
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Lecture 1B - Scheduler/Software/Storage
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<p>As shown in the previous note, high performance computing clusters are characterized by a (or several) login nodes.</p>
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Lecture 1C - Containers and R
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<time class="meta__text" datetime="2020-11-05T00:00:00">November 05, 2020</time>
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<p>OK, I listed this as R, then containers, but we will do R, containers then more R. Eh.</p>
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Lecture 1D - Going Parallel (Pleasingly)
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<p>Ok, the point to today’s discussion. Your <em>project</em> has exceeded what you can do locally. Possible reasons why:</p>
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Lecture 2A - Light introduction to Monte Carlo
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<p>Note, this is a BIG and important topic. I am barely scratching the surface to show that HPC is an important component due to the computational power required to run some of these models. Monte Carlo methods are ones that involve repeated random sampling to estimate unknown parameters.</p>
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Lecture 2B - Neural Networks
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<p>Neural networks are really a framework for building models. In recent years, these have gained major traction due in part to the popularity of machine learning.</p>
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Lecture 2C - R and Keras
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<p>Keras sits on top of TensorFlow (and others) and creates a high level abstraction of the underlying TensorFlow programming model.</p>
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