This blog contains additional content for the article "Advanced Vectorization" from Parallel Universe #12:
Intel recently unveiled the new Intel® Xeon Phi™ product – a coprocessor based on the Intel® Many Integrated Core architecture. Intel® Math Kernel Library (Intel® MKL) 11.0 introduces high-performance and comprehensive math functionality support for the Intel® Xeon Phi™ coprocessor. You can download the audio recording of the webinar and the presentation slides from the links below.
Salve a tutti,
è onore mio, di Community Manager di IDZ (Intel® Developer Zone™) per l'Italia, darvi il benvenuto nel nuovo portale dedicato a tutto il mondo software su architetture Intel.
The answer is "almost". There are two types of bugs: Reliability and Usability.
The Intel Intrinsics Guide is an interactive reference tool for Intel intrinsic instructions, which are C style functions that provide access to many Intel instructions – including Intel® Streaming SIMD Extensions [XX] (Intel® SSE[XX]), Intel® Advanced Vector Extensions (Intel® AVX), and more – without the need to write assembly code.
This guide provides searching and filtering functionality, in addition to reference information for every intrinsic. Reference information includes synopsis, description, functional operation, and corresponding instruction(s).
There are so many examples of applications using pre-processing strategy that it is trivial. For example using a webcam we often find the device driver doing some software adjustments and corrections such as white balancing. Too often we find devices using software features. Other examples would be in a pipeline and User Interfaces. When it comes to UI we already learned to fill the list when the user clicks the drop-down, so only when the user really wants to use the list we will "pay" for the data.
People say that GCC (GNU Compiler Collection) cannot generate effective code compared to other proprietary compilers. Is it a myth or reality? We will try to figure out how things really are with GCC. So, how can GCC compiler produce more effective code? We will describe some optional hints for x86 Linux platform "C", "C++" and "Fortran" compilation that help you get more performance from GCC. It should be useful for those customers and developers who need higher performance, but do not use proprietary compilers for various reasons.