Interesting message from https://blogs.oracle.com/R/ the latest R blog
Oracle just released the latest update to Oracle R Enterprise, version 1.1. This release includes the Oracle R Distribution (based on open source R, version 2.13.2), an improved server installation, and much more. The key new features include:
- Extended Server Support: New support for Windows 32 and 64-bit server components, as well as continuing support for Linux 64-bit server components
- Improved Installation: Linux 64-bit server installation now provides robust status updates and prerequisite checks
- Performance Improvements: Improved performance for embedded R script execution calculations
In addition, the updated ROracle package, which is used with Oracle R Enterprise, now reads date data by conversion to character strings.
We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for R-related software: Oracle R Distribution, Oracle R Enterprise, ROracle, Oracle R Connector for Hadoop. As always, we welcome comments and questions on the Oracle R Forum.
Oracle R Distribution 2-13.2 Update Available
Oracle has released an update to the Oracle R Distribution, an Oracle-supported distribution of open source R. Oracle R Distribution 2-13.2 now contains the ability to dynamically link the following libraries on both Windows and Linux:
- The Intel Math Kernel Library (MKL) on Intel chips
- The AMD Core Math Library (ACML) on AMD chips
To take advantage of the performance enhancements provided by Intel MKL or AMD ACML in Oracle R Distribution, simply add the MKL or ACML shared library directory to the LD_LIBRARY_PATH system environment variable. This automatically enables MKL or ACML to make use of all available processors, vastly speeding up linear algebra computations and eliminating the need to recompile R. Even on a single core, the optimized algorithms in the Intel MKL libraries are faster than using R’s standard BLAS library.
Open-source R is linked to NetLib’s BLAS libraries, but they are not multi-threaded and only use one core. While R’s internal BLAS are efficient for most computations, it’s possible to recompile R to link to a different, multi-threaded BLAS library to improve performance on eligible calculations. Compiling and linking to R yourself can be involved, but for many, the significantly improved calculation speed justifies the effort. Oracle R Distribution notably simplifies the process of using external math libraries by enabling R to auto-load MKL orACML. For R commands that don’t link to BLAS code, taking advantage of database parallelism usingembedded R execution in Oracle R Enterprise is the route to improved performance.
For more information about rebuilding R with different BLAS libraries, see the linear algebra section in the R Installation and Administration manual. As always, the Oracle R Distribution is available as a free download to anyone. Questions and comments are welcome on the Oracle R Forum.