CodeModernization

Meet the new 2nd-generation Intel® Xeon® Scalable processor family that’s already set 95 performance world records with new features including Intel® Deep Learning Boost (Intel® DL Boost) for AI deep learning inference acceleration and support for Intel® Optane™ DC (data center) persistent memory.

These days, memory systems use non-uniform memory access (NUMA) architectures, where cores and the total DRAM are divided among sockets. To achieve this, the Linux* kernel does NUMA migrations, which try to move memory pages to the sockets where the data is being accessed. There are tradeoffs. See where and discover how to maximize your performance

Explore Intel® Optane® DC persistent memory, a new technology that introduces a nonvolatile memory/storage tier that's faster than SSDs or hard drives, with latencies near DRAM and much larger capacity. It has implications for any workloads that are currently bound by memory capacity or the slow speeds of storage devices.

Get a real-world walkthrough of how to improve performance by enabling vectorization for PIC codes. Uses the particle class in Athena++, an astrophysical magnetohydrodynamics (MHD) code written in C++.

Optimizing the vectorization of your program is crucial to its performance. Learn how Intel® Advisor—a free, standalone tool—pinpoints vectorization issues and shows how well you’re using the hardware.

How your app accesses memory is crucial to performance. (Read: parallelization and vectorization aren’t enough.). Intel® Advisor helps you diagnose and fix memory issues. Take a deep dive into how it’s done.