Intel® DAAL is the library of commonly used building blocks for accelerating data analytics applications. It supports variety of usage scenarios ranging from doing analytics on IA-based mobile device or a sensor to running large scale distributed Big Data analysis on high performance clusters.
The library is targeting software developers who care about performance and power efficiency of their data analytics software as well as overall productivity. They don't need to spend days and months by implementing and optimizing commonly used data analysis algorithmic building blocks.
Intel DAAL is friendly to many data analytics application developers. Its API support C++ and Java* languages and allow software developers to seamlessly integrate DAAL with their C++ and Java applications and platforms to get great native code performance even in managed code environments.
Unlike other libraries targeting Machine Learning and Data Mining domains, Intel DAAL optimizes the entire workflow, from data acquisition from SQL* and no-SQL data sources to data transformations to data analysis, training and prediction.
Intel(R) Data Acceleration Analytics Library (Intel(R) DAAL) supports C++ Intel, MSFT*, and GNU compilers (please, see Release Notes of the library for the additional details on supported tools). While MinGW is not in the list of the supported compilers, we expect that Intel(R) DAAL based application might be built using MinGW compiler. Please, let us know, if you see any issue with this type of the compiler.