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AI for Any Environment, All the Time

In this special guest feature, our friends over at Advantech takes a look at the shift to edge computing environments versus large, secure data centers, a trend in stark contrast to the other end of the spectrum where large cloud providers and on-premise data centers offer a wide range of computing, networking and storage options within carefully controlled environments. Ultimately, we need both based on their respective value. But if we look deeper into what lies between the two extremes, we find the hybrid – rugged systems that bring the high-performance data center computing power and functionality to the edge. Advantech is a global leader in the fields of IoT intelligent systems and embedded platforms.

Precision Medicine pushes demand for HPC at the Edge: AI on the Fly ® Delivers

In this special guest feature, Tim Miller from One Stop Systems writes that by bringing specialized, high performance computing capabilities to the edge through AI on the Fly, OSS is helping the industry deliver on the enormous potential of precision medicine. “The common elements of these solutions are high data rate acquisition, high speed low latency storage, and efficient high performance compute analytics. With OSS, all of these building block elements are connected seamlessly with memory mapped PCI Express interconnect configured and customized as appropriate, to meet the specific environmental requirements of ‘in the field’ installations.”

Supermicro announces Pole-mounted Ruggedized Servers for AI on the Edge

Today Supermicro announced first-to-market IP65 enclosure-based servers for 5G RAN, AI inferencing, and other edge-focused applications based on Intel Xeon D and 2nd Gen Intel Xeon processors and broad configuration options. “Based on Supermicro’s Building Block Solutions, these 5G systems can be configured with a variety of processor and memory combinations so that customers can tailor their solutions to push data center remote management to the Edge. Supermicro has extensive experience with popular virtualization and container software such as Kubernetes, to efficiently facilitate these interactions, and has multiple servers certified NGC-Ready for Edge to extend AI capabilities across public and private networks.”

Gyrfalcon Acceleration Chips Speed SolidRun AI Inference Server

Today SolidRun introduced a new Arm-based AI inference server optimized for the edge. Highly scalable and modular, the Janux GS31 supports today’s leading neural network frameworks and can be configured with up to 128 Gyrfalcon Lightspeeur SPR2803 AI acceleration chips for unrivaled inference performance for today’s most complex video AI models. “While GPU-based inference servers have seen significant traction for cloud-based applications, there is a growing need for edge-optimized solutions that offer powerful AI inference with less latency than cloud-based solutions. Working with Gyrfalcon and utilizing their industry-proven ASICs has allowed us to create a powerful, cost-effective solution for deploying AI at the Edge that offers seamless scalability.”

Michela Taufer presents: Scientific Applications and Heterogeneous Architectures

Michela Taufer from UT Knoxville gave this talk at ATPESC 2019. “This talk discusses two emerging trends in computing (i.e., the convergence of data generation and analytics, and the emergence of edge computing) and how these trends can impact heterogeneous applications. This talk presents case studies of heterogenous applications in precision medicine and precision farming that expand scientist workflows beyond the supercomputing center and shed our reliance on large-scale simulations exclusively, for the sake of scientific discovery.”

High Speed Data Capture for AI on the Fly Edge Applications

In many AI applications, transporting large amounts of data back to a remote datacenter is impractical and undesirable. With AI on the Fly, the entire AI workflow resides at the edge at the data source. One Stop Systems’s Tim Miller explores how high performance scalable data acquisition is a fundamental and enabling component of this emerging new paradigm. 

Supermicro steps up with NVIDIA EGX for AI on the Edge

Today Supermicro announced support for the NVIDIA EGX platform, allowing customers to rapidly develop AI applications in their Edge networks. “Enhancing our GPU servers and advanced platforms optimized for AI at the Edge technology with NVIDIA EGX and NGC provides a wide selection of optimized and efficient solutions for the intelligent Edge and for seamless integration from the Edge to the cloud.”

NVIDIA EGX Accelerates AI on TYAN Edge Server

Today TYAN announced that it is teaming with NVIDIA to integrate the NVIDIA EGX platform with its Thunder SX TN76-B7102 edge server, completing TYAN’s GPU server product line. “NVIDIA EGX provides the missing link for low-latency AI computing at the edge with an advanced, light-compute platform, reducing the amount of data that needs to be pushed to the cloud.”

Quadric.io to Build “Supercomputer for Edge Devices”

Today chip startup Quadric.io announced plans to build the world’s first “supercomputer” specifically designed for the real-time needs of autonomous systems. “Instead of building a heterogeneous system with CPUs/GPUs/FPGAs & AI chips and dealing with that complexity of software and hardware integration, Quadric has the technology to handle most of the application in a single unified hardware architecture and software model.”

Qualcomm to bring power-efficient AI Inference to the Cloud

Today Qualcomm announced that it is bringing the Company’s artificial intelligence expertise to the cloud with the Qualcomm Cloud AI 100. “Our all new Qualcomm Cloud AI 100 accelerator will significantly raise the bar for the AI inference processing relative to any combination of CPUs, GPUs, and/or FPGAs used in today’s data centers,” said Keith Kressin, senior vice president, product management, Qualcomm Technologies, Inc.