Book description
Moore’s law has finally run out of steam for CPUs. The number of x86 cores that can be placed cost-effectively on a single chip has reached a practical limit, making higher densities prohibitively expensive for most applications. Fortunately, for big data analytics, machine learning, and database applications, a more capable and cost-effective alternative for scaling compute performance is already available: the graphics processing unit, or GPU.
In this report, executives at Kinetica and Sierra Communications explain how incorporating GPUs is ideal for keeping pace with the relentless growth in streaming, complex, and large data confronting organizations today. Technology professionals, business analysts, and data scientists will learn how their organizations can begin implementing GPU-accelerated solutions either on premise or in the cloud.
This report explores:
- How GPUs supplement CPUs to enable continued price/performance gains
- The many database and data analytics applications that can benefit from GPU acceleration
- Why GPU databases with user-defined functions (UDFs) can simplify and unify the machine learning/deep learning pipeline
- How GPU-accelerated databases can process streaming data from the Internet of Things and other sources in real time
- The performance advantage of GPU databases in demanding geospatial analytics applications
- How cognitive computing—the most compute-intensive application currently imaginable—is now within reach, using GPUs
Table of contents
- Introduction
- 1. The Evolution of Data Analytics
- 2. GPUs: A Breakthrough Technology
- 3. New Possibilities
- 4. Machine Learning and Deep Learning
- 5. The Internet of Things and Real-Time Data Analytics
- 6. Interactive Location-Based Intelligence
- 7. Cognitive Computing: The Future of Analytics
- 8. Getting Started
Product information
- Title: Introduction to GPUs for Data Analytics
- Author(s):
- Release date: October 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491998038
You might also like
book
Advances in GPU Research and Practice
Advances in GPU Research and Practice focuses on research and practices in GPU based systems. The …
book
Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to …
audiobook
What's New in AI: Open Source Large Language Models with Eric Xing (Audio)
Join host George Anadiotis and guest Eric Xing, for a discussion about the current and expanding …
book
Machine Learning Pocket Reference
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of …