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Software-Defined Visualization with Intel Rendering Framework – No Special Hardware Needed

This sponsored post from Intel explores how the Intel Rendering Framework, which brings together a number of optimized, open source rendering libraries, can deliver better performance at a higher degree of fidelity — without having to invest in extra hardware. By letting the CPU do the work, visualization applications can run anywhere without specialized hardware, and users are seeing better performance than they could get from dedicated graphics hardware and limited memory. 

‘AI on the Fly’: Moving AI Compute and Storage to the Data Source

The impact of AI is just starting to be realized across a broad spectrum of industries. Tim Miller, Vice President Strategic Development at One Stop Systems (OSS), highlights a new approach — ‘AI on the Fly’ — where specialized high-performance accelerated computing resources for deep learning training move to the field near the data source. Moving AI computation to the data is another important step in realizing the full potential of AI.

Intel Addresses the Convergence of AI, Analytic, and Traditional HPC Workloads

HPC is no longer just HPC, but rather a mix of workloads that instantiate the convergence of AI, traditional HPC modeling and simulation, and HPDA (High Performance Data Analytics). Exit the traditional HPC center that just runs modeling and simulation and enter the world that must support the convergence of HPC-AI-HPDA computing, and sometimes with specialized hardware. In this sponsored post, Intel explores how HPC is becoming “more than just HPC.”

GPUs for Oil and Gas Firms: Deriving Insights from Petabytes of Data

Adoption of GPU-accelerated computing can offer oil and gas firms significant ROI today and pave the way to gain additional advantage from future technical developments. To stay competitive, these companies need to be able to derive insights from petabytes of sensor, geolocation, weather, drilling, and seismic data in milliseconds. A new white paper from Penguin Computing explores how GPUs are spurring innovation and changing how hydrocarbon businesses address data processing needs.

Making Python Fly: Accelerate Performance Without Recoding

Developers are increasingly besieged by the big data deluge. Intel Distribution for Python uses tried-and-true libraries like the Intel Math Kernel Library (Intel MKL)and the Intel Data Analytics Acceleration Library to make Python code scream right out of the box – no recoding required. Intel highlights some of the benefits dev teams can expect in this sponsored post.

Best Practices for Building, Deploying & Managing HPC Clusters

In today’s markets, a successful HPC cluster can be a formidable competitive advantage. And many are turning to these tools to stay competitive in the HPC market. That said, these systems are inherently very complex, and have to be built, deployed and managed properly to realize their full potential. A new report from Bright Computing explore best practices for HPC clusters. 

Turbocharge your HPC Hybrid Cloud with Policy-based Automation

While there are many advantages to running in the cloud, the issues can be complex. Users need to figure out how to securely extend on-premise clusters, devise solutions for data handling and constantly keep an eye on costs. Univa’s Robert Lalonde, Vice President and General Manager, Cloud, explores how to turbocharge your HPC hybrid cloud with tools like policy-based automation, and how closing the loop between workload scheduling and cloud-automation can drive higher performance and dramatic cost efficiencies.

CPU, GPU, FPGA, or DSP: Heterogeneous Computing Multiplies the Processing Power

Whether your code will run on industry-standard PCs or is embedded in devices for specific uses, chances are there’s more than one processor that you can utilize. Graphics processors, DSPs and other hardware accelerators often sit idle while CPUs crank away at code better served elsewhere. This sponsored post from Intel highlights the potential of Intel SDK for OpenCL Applications, which can ramp up processing power.

Data Management: The Elephant in the Room for HPC Hybrid Cloud

While there are many benefits to leveraging the cloud for HPC, there are challenges as well. Along with security and cost, data handling is consistently identified as a top barrier. “In this short article, we discuss the challenge of managing data in hybrid clouds, offer some practical tips to makes things easier, and explain how automation can play a key role in improving efficiency.”

AI Critical Measures: Time to Value and Insights

AI is a game changer for industries today but achieving AI success contains two critical factors to consider — time to value and time to insights.  Time to value is the metric that looks at the time it takes to realize the value of a product, solution or offering. Time to insight is a key measure for how long it takes to gain value from use of the product, solution or offering.