Resources

Learn how to improve scalability for Intel® Xeon® and Intel® Xeon Phi™ processors using new Intel® VTune™ Amplifier memory analysis.

Explore a real-world case study of HPC application tuning using several of the tools in Intel® Parallel Studio XE for optimizing SPECFEM3D_GLOBE* performance on Intel® architecture.

ANNs, CNNs, and DNNs—See why Intel® Math Kernel Library, Intel® Threading Building Blocks, and OpenMP* are instrumental in optimizing deep learning software.

Find out how the latest Intel® MKL Compact functions—six of them to be precise—deliver vectorization-based optimizations for HPC apps that depend on matrix computations on large groups of very small matrices.

LeCloud, a global video cloud service provider, is the subject of this study that explains how compiling MySQL with the Intel C++ Compiler can significantly improve database performance.

One of the most common applications of outlier detection—credit card fraud—is presented to show how the Intel® Data Analytics Acceleration Library is used to achieve high performance and high accuracy.

Today’s business applications―such as analytics and deep learning—require extensive numerical computing. New enhancements to Java* enable optimized performance with the latest Intel® Xeon® processors.

Utilizing Intel® Advisor, part of Intel® Parallel Studio XE, is a powerful way to generate program statistics that can help you optimize your system with vectorized and threaded code.

Vectorization is having a renaissance (like you didn’t know). Get an overview of this resurging mainstay and best practices for using it to speed code as implemented in WARP3D.