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**Compute.scala** is a Scala library for scientific computing with N-dimensional arrays in parallel on GPU, CPU and other devices. It will be the primary back-end of the incoming [DeepLearning.scala](http://deeplearning.thoughtworks.school/) 3.0, to address performance problems we encountered in DeepLearning.scala 2.0 with [ND4J](http://ND4J.org/).
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* Compute.scala can dynamically merge multiple operators into one kernel program, which runs significantly faster when performing complex computation.
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* Compute.scala manages data buffers and other native resources in a determinate approach, consuming less memory.
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* Compute.scala manages data buffers and other native resources in a determinate approach, consuming less memory and reducing the performance impact of garbage collection.
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* All dimensional transformation operators (`permute`, `broadcast`, `reshape`, etc) in Compute.scala are views, with no additional data buffer allocation.
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* N-dimensional arrays in Compute.scala can be converted from / to JVM collection, which support higher-ordered functions like `map` / `reduce`, and still can run on GPU.
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