We are pleased to announce the release of Intel® Data Analytics Acceleration Library 2016 Beta! Intel® Data Analytics Acceleration Library is a C++ and Java API library of optimized analytics building blocks for all data analysis stages, from data acquisition to data mining and machine learning. It is a library essential for engineering high performance data application solutions. Click here to see more.
Intel MKL Users,
We would like to Introduce a new feature Intel® MKL Cookbook, an online Document with recipes for assembling Intel MKL routines for solving complex problems.Please give us your valuable feedback on these Cookbook recipes, and let us know if you want us to include more recipes and/or improve existing recipes.
Thank you for Evaluating
Intel MKL Team
Intel MKL users,
We would like to hear from you how you are using Intel MKL with threading. Do you use the parallel or sequential MKL? How do your multithreaded applications use MKL? We would appreciate you to complete a short survey. It takes no more than 5 minutes. Your feedback will help us to make Intel MKL a better product. Thanks!
Survey link: https://idz.qualtrics.com/SE/?SID=SV_5Bmh232m96WJK3b
We have been using the following code compiled with Intell Fortran on Linux clusters linked with MKL 10.2.2.025 for a number of years. We are trying to update to Intel 15 compilers and MKL 11.2 update 2. The symmetric solve produces wrong answers using the new compiler and libraries. The code has not changed. When we include the symmetric terms and solve it as a symmetric_structure matrix we get the right answers.
Is any one else having problems with symmetric solves with the current compiler and library?
Load the data into indx, vall, and y_rt ...
I have "old" codes that call Fortran numerical_libraries routine GQRUL and DGQRUL for calculating Gauss-Legendre quadrature rule to perform numerical integration. I used to be able to just put a line in the main routine "USE numerical_libraries" and subsequently was able to call GQRUL and DGQRUL functions.
I have been trying to optimize matrix multiplication on NUMA systems but so far without much luck.
I have played around with the dgemm routine and first touch.
A snippet of my code looks like this:
Is the Parallel Direct Sparse Solver for Clusters supported on Windows OS?
- Стр. 1