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SkyScale: GPU Cloud Computing with a Difference

In this guest post, Tim Miller, president of SkyScale, covers how GPU cloud computing is on the fast track to crossing the chasm to widespread adoption for HPC applications. “Two good examples of very different markets adopting GPU computing and where cloud usage makes sense are artificial intelligence and high quality rendering.”

How AI & Machine Intelligence is Assisting Clinicians

According to a new Ovum white paper, sponsored by NVIDIA, there is a huge opportunity to help physicians with AI-based systems that can cut down on the workload across protocoling, imaging analysis, and automated reporting of the results.

NVIDIA Offers Framework to Solve AI System Challenges

At the recent NVIDIA GPU Technology Conference (GTC) 2018, Jensen Huang, NVIDIA President and CEO, during his presentation focused on a new framework designed to contextualize the key challenges using AI systems and delivering deep learning-based solutions. A new white paper sponsored by NVIDIA outlines these requirements — coined PLASTER.

Bing Uses NVIDIA GPUs, Tech to Enhance Object Detection and Image Search

Object detection and image search is seen as the next big thing when it comes to the search sector. And it’s easy to see why. A new white paper from NVIDIA explores how Bing deployed NVIDIA GPUs and technology to speed up object detection and visual search capabilities.

Unified Deep Learning Configurations and Emerging Applications

This is the final post in a five-part series from a report exploring the potential machine and a variety of computational approaches, including CPU, GPU and FGPA technologies. This article explores unified deep learning configurations and emerging applications. 

Unified Deep Learning with CPU, GPU and FPGA Technologies

Deep learning and complex machine learning has quickly become one of the most important computationally intensive applications for a wide variety of fields. Download the new paper — from Advanced Micro Devices Inc. (AMD) and Xilinx Inc. — that explores the challenges of deep learning training and inference, and discusses the benefits of a comprehensive approach for combining CPU, GPU, FPGA technologies, along with the appropriate software frameworks in a unified deep learning architecture.

Rack Scale Composable Infrastructure for Mixed Workload Data Centers

A more flexible, application-centric, datacenter architecture is required to meet the needs of rapidly changing HPC applications and hardware. In this guest post, Katie Rivera of One Stop Systems explores how rack-scale composable infrastructure can be utilized for mixed workload data centers. 

NVIDIA Makes Visualization Easier in the Cloud

Visualizing the results of a simulation can give new insight into complex scientific problems. Interactive viewing of entire datasets can lead to earlier understanding of the challenge at hand and can enhance the understanding of complex phenomena. With the release of the of HPC Visualization Containers with the NVIDIA CPU Cloud, it has become much easier to get a visualization system up and production ready much quicker than ever before.

Composable Infrastructure: Composing Greater HPC Breakthroughs

Composable infrastructure allows any number of CPU nodes to dynamically map the optimum number of GPU and NVMe storage resources to each node required to complete a specific task.  In this sponsored post, Katie Rivera of One Stop Systems, explores the power of GPUs and the potential benefits of composable infrastructure for HPC. 

Modernizing Healthcare Workloads with Virtual GPU Technology

In the healthcare sector, clinicians are increasingly using mobile devices such as smartphones, tablets, and personal laptops to access patient records and more. Many hospitals have turned to virtualization and virtual GPU technology to offer greater mobility, security, and IT manageability. Download the report from HPE that explores how virtual GPU technology is modernizing healthcare.