Go with Intel® Data Analytics Acceleration Library and Go*

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The Go gopher by Renee French

Use of the Go* programming language and it’s developer community has grown significantly since it’s official launch by Google in 2009. Like many popular programming languages (C and Java come to mind), Go started as an experiment to design a new programming language that would fix some of the common problems of other languages and yet stay true to the basic tenets of modern programming: be scalable, productive, readable, enable robust development environments, and support networking and multiprocessing.

Because it is fast, easy to learn and deploy, and comes with a vast DevOps toolchain, Go, not surprisingly, is turning out to be the go to language for web services and devops. And with businesses becoming more data driven, employing intense computational applications at nearly every level of their operations, we see Go being called on to integrate machine learning with distributed data transformation and online analysis. So connecting Go programs to the Intel® Data Analytics Acceleration Library (Intel® DAAL) is a match made for Big Data and High Performance Computing.

Intel DAAL is a highly optimized library of computationally intensive routines supporting Intel architectures including Intel Xeon® processors, Intel Core processors, Intel Atom processors and Intel Xeon Phi™ processors. Intel DAAL provides a rich set of algorithms, ranging from the most basic descriptive statistics for datasets to more advanced data mining and machine learning algorithms.

Because Go features an efficient interface to C/C++, Go programs can easily utilize the Intel DAAL for robust, scalable, and high performant data processing without much trouble.  This means that Go developers can immediately take advantage of the features and optimizations of the Intel DAAL library right out of the box. Shown to give a substantial performance boost over alternatives, big data developers programming in Go are discovering that with Intel DAAL they can implement batch, online, and distributed neural networks, clustering, and much more right within their Go applications.

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To call Intel DAAL library routines from within a Go program you need a tool called cgo to interoperate Go code with the library. Cgo comes with the Go programming environment. The programmer provides definition and declaration files that wrap the Intel DAAL functions Go program calls. And with another free and open source tool called SWIG* that connects C/C++ programs with a variety of high-level programming languages, including Go, you can build a reusable Go package that wraps the Intel DAAL routines an application needs.

With Intel DAAL, and tools like cgo and SWIG, you can now create powerful portable apps and packages for Big Data and data science by programming in a fast, easy to learn DevOps programming language: Go!


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