Sign up for our newsletter and get the latest HPC news and analysis.
Send me information from insideHPC:


The New Nvidia HGX-1: GPU Power for Machine Learning at Hyperscale

Rob Ober from Nvidia describes the company’s new HGX-1 reference platform for GPU computing. “Powered by NVIDIA Tesla GPUs and NVIDIA NVLink high-speed interconnect technology; the HGX-1 comes as AI workloads—from autonomous driving and personalized healthcare to superhuman voice recognition—are taking off in the cloud.”

Supermicro Showcases Powerful GPU Solutions at GTC 2017

In this video from GTC 2017, Rudolfo Campos from Supermicro describes the company’s innovative solutions for GPU-accelerated computing. “Leveraging our extensive portfolio of GPU solutions, customers can massively scale their compute clusters to accelerate their most demanding deep learning, scientific and hyperscale workloads with fastest time-to-results, while achieving maximum performance per watt, per square foot, and per dollar.”

Eric Barton Joins DDN as CTO for Software-Defined Storage

Today DDN appointed Eric Barton as the company’s chief technology officer for software-defined storage. In this role, Barton will lead the company’s strategic roadmap, technology architecture and product design for DDN’s newly created Infinite Memory Engine business unit. Barton brings with him more than 30 years of technology innovation, entrepreneurship and expertise in networking, distributed systems and storage software.

Drilling Down into Machine Learning and Deep Learning

Artificial intelligence and machine learning are rising in popularity as the needs of big data call for systems that exceed human capabilities. This article is part of a special insideHPC report that explores trends in machine learning and deep learning.

Choosing the Right In-Memory Computing Solution

This white paper reviews why IMC makes sense for today’s fast-data and big-data applications, dispels common myths about IMC, and clarifies the distinctions among IMC product categories to make the process of choosing the right IMC solution for a specific use case much easier. Download now to learn more.

insideHPC Special Report Riding the Wave of Machine Learning & Deep Learning

AI, machine learning and deep learning are transforming the entire world of technology, but these technologies are only making headway now due to the proliferation of data. Companies first steps should include the “Five-step enterprise AI strategy”. To learn more about riding the wave of machine learning and deep learning download this insideHPC special report.

Intel Processors for Machine Learning

Machine Learning is a hot topic for many industries and is showing tremendous promise to change how we use systems. From design and manufacturing to searching for cures for diseases, machine learning can be a great disrupter, when implemented to take advantage of the latest processors.

OpenPOWER Developer Congress Event to Focus on Machine Learning

Today IBM announced that the first annual OpenPOWER Foundation Developer Congress will take place May 22-25 in San Francisco. With a focus on Machine Learning, the conference will focus on continuing to foster the collaboration within the foundation to satisfy the performance demands of today’s computing market.

Slidecast: ARM Steps Up to Machine Learning

In this slidecast, Jem Davies (VP Engineering and ARM Fellow) gives a brief introduction to Machine Learning and explains how it is used in devices such as smartphones, autos, and drones. “I do think that machine learning altogether is probably going to be one of the biggest shifts in computing that we’ll see in quite a few years. I’m reluctant to put a number on it like — the biggest thing in 25 years or whatever,” said Jem Davies in a recent investor call. “But this is going to be big. It is going to affect all of us. It affects quite a lot of ARM, in fact.”

Intel DAAL Accelerates Data Analytics and Machine Learning

Intel DAAL is a high-performance library specifically optimized for big data analysis on the latest Intel platforms, including Intel Xeon®, and Intel Xeon Phi™. It provides the algorithmic building blocks for all stages in data analysis in offline, batch, streaming, and distributed processing environments. It was designed for efficient use over all the popular data platforms and APIs in use today, including MPI, Hadoop, Spark, R, MATLAB, Python, C++, and Java.