A Mission-Critical Big Data Platform for the Real-Time Enterprise

As the volume and velocity of enterprise data continue to grow, extracting high-value insight is becoming more challenging and more important. Businesses that can analyze fresh operational data instantly—without the delays of traditional data warehouses and data marts—can make the right decisions faster to deliver better outcomes.
Authored by Nguyen, Khang T (Intel) Last updated on 06/07/2017 - 09:29

Evaluating the Power Efficiency and Performance of Multi-core Platforms Using HEP Workloads

As Moore’s Law drives the silicon industry towards higher transistor counts, processor designs are becoming more and more complex. The area of development includes core count, execution ports, vector units, uncore architecture and finally instruction sets. This increasing complexity leads us to a place where access to the shared memory is the major limiting factor, resulting in feeding the cores...
Authored by Mike P. (Intel) Last updated on 06/07/2017 - 10:43

Understanding NUMA for 3D isotropic Finite Difference (3DFD) wave equation code

This article demonstrates techniques that software developers can use to identify and fix NUMA-related performance issues in their applications using the latest Intel® software development tools.
Authored by Sunny G. (Intel) Last updated on 06/01/2017 - 11:19

How NUMA Affects your Workloads: Intel® VTune™ Amplifier

Many modern multi-socket systems are based on non-uniform memory access (NUMA), where access latency and bandwidth depend on the location of the physical memory relative to its use.

Authored by Bhanu Shankar (Intel) Last updated on 06/14/2017 - 08:55

Performance Improvement Opportunities with NUMA Hardware

Intel’s non-uniform memory access (NUMA) strategy is based on several new memory technologies that promise significant improvements in both capability and performance. This article provides information on Multi-Channel DRAM (MCDRAM) and High-Bandwidth Memory (HBM), Non-volatile dual inline-memory modules (NVDIMMs), and Intel® Omni-Path Fabric (Intel® OP Fabric).
Authored by Bevin B. (Intel) Last updated on 06/20/2016 - 11:11

NUMA Hardware Target Audience

Do you have a problem that Intel non-uniform memory access (NUMA) hardware and the related tools and strategies can solve? The answer depends on the problem you are facing and if you can make decisions about choosing/changing your hardware, your software, or both. This article walks you through the decision.
Authored by Bevin B. (Intel) Last updated on 06/20/2016 - 11:11

Hardware and Software Approach for Using NUMA Systems

Learn how to build an application that runs effectively on non-uniform memory access (NUMA) hardware. This article walks you through choosing the algorithm all the way through to measuring your application's performance.
Authored by Bevin B. (Intel) Last updated on 08/13/2016 - 05:50

What’s New about Modern Hardware

New non-uniform memory access (NUMA) technologies are spreading across processors populating the modern computing world – whether those processors are in individual servers designed to run small applications, or in massive dedicated MPI clusters.
Authored by Bevin B. (Intel) Last updated on 10/27/2016 - 13:18

3D Isotropic Acoustic Finite-Difference Wave Equation Code: A Many-Core Processor Implementation and Analysis

Finite difference is a simple and efficient mathematical tool that helps solve differential equations.

Authored by Sunny G. (Intel) Last updated on 05/08/2017 - 06:49
Blog post

Optimizing Software Applications for NUMA: Part 7 (of 7)


Authored by David Ott (Intel) Last updated on 06/14/2017 - 15:36
For more complete information about compiler optimizations, see our Optimization Notice.