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Viral B Shah - The Many Ways Of Parallel Computing With Julia

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Julia is a high performance dynamic language, primarily designed for technical computing, but increasingly seeing applications in a wide variety of domains.

This talk will provide an overview of parallel computing in Julia. It will start with an introduction to using built-in Julia primitives for parallel processing, such as pmap, @parallel, remotecall, spawn, fetch, etc. Based on this low-level primitives, shared arrays and distributed arrays have been built. We will try some Parallel Linear Algebra using packages such as ScaLapack along with some MPI programming. We will also look at the possibilities of data processing with data loaded from the Hadoop file system (HDFS) and/or S3. We will also preview the upcoming multi-threading capabilities in Julia.
Category
Computing
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