White Papers

Comparing CPUs and GPUs for Deep Learning and Artificial Intelligence

March 30, 2021 | BY: Tammy Carter

Download PDF

At its Data-Centric Innovation Day in April 2019, Intel introduced its new 2nd Generation Xeon® Scalable Processors. Equipped with features for machine learning and artificial intelligence (AI), such as Intel Deep Learning Boost (Intel DL Boost) and Vector Neural Network Instruction (VNNI), these CPUs strengthened Intel’s play in an increasingly emerging technology space where NVIDIA GPUs have held the dominant position.

In this white paper, we examine Intel’s 2nd Generation Xeon Scalable Processors with NVIDIA’s V100 and T4 GPUs, looking at comparisons using three different benchmarks and extrapolating to understand both technologies’ potential in defense and aerospace AI-based applications.

Read the full white paper to explore

  • Intel CPUs’ and NVIDIA GPUs’ capabilities for deep learning
  • Inference performance comparisons using ResNet-50, BERT, and NCF benchmarks
  • Whether a CPU or GPU is better for aerospace and defense AI applications

Related Content

Author’s Biography

Tammy Carter

Senior Product Manager – GPGPUs & Software

Tammy Carter is the Senior Product Manager for GPGPUs and software products, featuring OpenHPEC, for Curtiss-Wright Defense Solutions. In addition to a M.S. in Computer Science, she has over 20 years of experience in designing, developing and integrating real-time embedded systems in the Defense, Communications and Medical arenas.

Share This Article

  • Share on Linkedin
  • Share on Twitter
  • Share on Facebook
  • Share on Google+
Connect With Curtiss-Wright Connect With Curtiss-Wright Connect With Curtiss-Wright
Sales

CONTACT SALES

Contact our sales team today to learn more about our products and services.

YOUR LOCATION

PRODUCT INFORMATION

Support

GET SUPPORT

Our support team can help answer your questions - contact us today.

REQUEST TYPE

SELECT BY

SELECT Topic