Intel® Math Kernel Library (Intel® MKL) is a computational math library aimed at unleashing performance on Intel® architecture. Designed for scientific, engineering, and financial applications, it efficiently handles both very small and very large computations.
Join us for an in-depth look at software development for embedded, mobile, and the Internet of Things.
As systems grow in complexity due to the number and type of cores, and vector size, you need to develop and update code to ensure scalability and take advantage of current and next-gen platforms.
Learn how to build and optimize imaging, in-vehicle infotainment (IVI), long-term evaluation reference design, and surveillance applications on Intel® architecture using different components of Intel® System Studio.
A close look at software-based power analysis solutions on Intel® architecture-based systems.
A JTAG debugger can be a great tool in kernel module development. Advantages include halting the complete system during debugging (not only the thread being debugged), and making it easy to examine the entire CPU and memory.
Processor graphics hardware occupies almost 30% of the processor silicon real estate. This makes it all the more important to expose these computation units to developers for general-purpose computing and unlock the idle GFLOPS in Intel® Graphics Technology.
The vectorization features of the Intel compiler continue to get more powerful with each succeeding version.
The free ride of faster performance with increased clock speeds is long gone. Software must be both threaded and vectorized to fully utilize today’s and tomorrow’s hardware.
This article introduces the implementation of the submodule feature new in Intel® Fortran in compiler version 16.0. This allows modification of submodules without recompiling every source that uses a module.