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Document Library offers reference architectures, whitepapers, and solutions briefs to help build and enhance your network infrastructure, at any level of deployment.
As edge networks support a wider range of workloads, Cloudify Spire adds Enhanced Platform Awareness for Kubernetes to intelligently place software that needs special hardware capabilities.
Published On: February 14, 2020
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Deliverables - Hardware Platforms, Integrated Solutions, Services, Software Platforms | Intel Technologies and Platforms - Accelerators, Fabric | Network Location - Data Center, Device Edge, Metro/Regional CO Edge, On Premises, Remote CO Edge, Access Edge | NFVI - Hardware, OS/Virtualization | Orchestration and Network Management - Virtualized Infrastructure Manager (VIM), NFV Service Orchestration | System Integrators - System Integrators | Verticals / Industries - Connected Cars, Financial Services, Industrial, Manufacturing, Media & Entertainment, Medical / Healthcare, Retail, Smart Cities, Transportation | Virtual Network Functions - Content Optimization, Content Delivery Networks (CDN), Policy Controllers & Policy Charging Rules Function (PCRF), IP Multimedia Subsystem (IMS), CPE, Session Border Controller (SBC), Application Delivery Controller (ADC), Load Balancer (LB), Security Appliances / Security Software / Intrusion Prevention System (IPS) / Intrusion Detection System (IDS), Wide Area Network (WAN) Optimization, Deep Packet Inspection (DPI) / Traffic Firewall, Virtualized Evolved Packet Core (vEPC), Router, Broadband Remote Access Server (BRAS), Multi-access Edge Computing (MEC), Virtualized Radio Access Network (vRAN) | Workloads and Use Cases - Analytics, Artificial Intelligence, Augmented/Virtual Reality, Computer Vision, Content Distribution, Crowd Sensing, Emergency Response, Security, Virtualized Small Cell Gateway, uCPE/vCPE
As edge networks support a wider range of workloads, Cloudify Spire adds Enhanced Platform Awareness for Kubernetes to intelligently place software that needs special hardware capabilities.
Operations at the edge can be very complex, expensive, inconsistent and labor intensive. Pivot Technology Services solves this through SaaS-like software deployments with security features that enable impactful AI experiences with Intel® edge technology.
Published On: February 11, 2020
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Deliverables - Services | Intel Technologies and Platforms - Intel Xeon processor | Workloads and Use Cases - Artificial Intelligence, Computer Vision
Operations at the edge can be very complex, expensive, inconsistent and labor intensive. Pivot Technology Services solves this through SaaS-like software deployments with security features that enable impactful AI experiences with Intel® edge technology.
Describe utilizing NFV demo framework to save the collected data and play it back any time anywhere in an intuitive a data visualization environment. Help us to better understand the performance benefit of Intel processor, without a full investment of expensive traffic generator and full hardware BOM of a NFV system.
Published On: February 10, 2020
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NFVI - Hardware, OS/Virtualization | System Integrators - System Integrators | Test Tools and Reporting Software - Test Tools & Reporting Software
Describe utilizing NFV demo framework to save the collected data and play it back any time anywhere in an intuitive a data visualization environment. Help us to better understand the performance benefit of Intel processor, without a full investment of expensive traffic generator and full hardware BOM of a NFV system.
NoviFlow CyberMapper provides security load balancing and mitigation services for high-throughput networks. The NoviFlow solution utilizes Barefoot Networks Tofino™-based switches rated for up to 6.5 terabit-per-second performance.
NoviFlow CyberMapper provides security load balancing and mitigation services for high-throughput networks. The NoviFlow solution utilizes Barefoot Networks Tofino™-based switches rated for up to 6.5 terabit-per-second performance.
This white paper looks at the transformation under way in AI-powered contact centers and the platform requirements for successful implementations. One such implementation shows how Scalable processors help accelerate conversational solutions from AI Builders member, Gnani.ai.
Published On: February 05, 2020
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Application Type - Machine Learning | Compute - Intel® Xeon Scalable | Deployment Channel - CSP - Amazon Web Services, CSP - Google Cloud, On-premise (Private Cloud, Other) | Framework Optimizations - TensorFlow | Industry - Automotive, Cross-Industry, Finance and Insurance, Government, Real Estate, Rental and Leasing, Communications | Model Training - Models cant be re-trained - Inference only | Offering Type - AI Software/SaaS | Operating System - Linux | Software Libraries - Intel® Distribution for Python | Solution Geographic Availability - Worldwide | Topology - Proprietary | Use Case - Conversational Bots and Voice Agents
This white paper looks at the transformation under way in AI-powered contact centers and the platform requirements for successful implementations. One such implementation shows how Scalable processors help accelerate conversational solutions from AI Builders member, Gnani.ai.
Tests with colocated packet-processing network functions show the NFV Service Assurance Platform using Intel® Resource Director Technology optimizes cache allocation for deterministic VNF performance and lower latency.
Published On: February 05, 2020
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Deliverables - Hardware Platforms, Integrated Solutions, Services, Software Platforms | Intel Technologies and Platforms - Intel Xeon D processor, Accelerators, Fabric, Intel Atom processor, Intel Xeon processor, Memory, SSD | Network Location - Device Edge, Metro/Regional CO Edge, On Premises, Remote CO Edge, Access Edge , Data Center | NFVI - Hardware, OS/Virtualization | Orchestration and Network Management - Virtualized Infrastructure Manager (VIM), NFV Service Orchestration, OSS, BSS & EMS / NMS, SDN Controller | System Integrators - System Integrators | Test Tools and Reporting Software - Test Tools & Reporting Software | Verticals / Industries - Connected Cars, Financial Services, Industrial, Manufacturing, Media & Entertainment, Medical / Healthcare, Retail, Smart Cities, Transportation | Virtual Network Functions - Virtualized Evolved Packet Core (vEPC), Virtualized Radio Access Network (vRAN) | Workloads and Use Cases - Analytics, Artificial Intelligence, Augmented/Virtual Reality, Computer Vision, Content Distribution, Crowd Sensing, Emergency Response, Security, Virtualized Small Cell Gateway, uCPE/vCPE
Tests with colocated packet-processing network functions show the NFV Service Assurance Platform using Intel® Resource Director Technology optimizes cache allocation for deterministic VNF performance and lower latency.
IBC 360 Live system initiated by Tiledmedia and Intel live streamed the five-day IBC 2019 conference globally in 8K, 360 degree virtual reality (VR). Use of tiled streaming technology reduces bandwidth requirements making it a key enabler of high-resolution 8K VR streaming.
Published On: February 05, 2020
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Workloads and Use Cases - Augmented/Virtual Reality
IBC 360 Live system initiated by Tiledmedia and Intel live streamed the five-day IBC 2019 conference globally in 8K, 360 degree virtual reality (VR). Use of tiled streaming technology reduces bandwidth requirements making it a key enabler of high-resolution 8K VR streaming.
This solution brief highlights how ZeroFOX uses the Intel Distribution of OpenVINO toolkit to accelerate their threat detection and bring value to their customers.
Published On: January 29, 2020
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Application Type - Machine Learning, Deep Learning, Other | Compute - Intel® Xeon Scalable | Deployment Channel - CSP - Amazon Web Services | Framework Optimizations - Custom/Other | Industry - Cross-Industry | Model Training - Models can be trained - requires labeled data | Offering Type - AI Software/SaaS | Operating System - Linux | Software Libraries - Compute Library for Deep Neural Networks (clDNN) | Solution Geographic Availability - Worldwide | Toolkits - Intel® Distribution of OpenVINO™ toolkit | Topology - Yolo | Use Case - Image/Object Detection/Recognition/Classification
This solution brief highlights how ZeroFOX uses the Intel Distribution of OpenVINO toolkit to accelerate their threat detection and bring value to their customers.
This reference architecture outlines how combining H2O.ai products, 2nd generation Intel Xeon Scalable processors, and Intel DC SSDs can decrease training time and inference time without sacrificing model accuracy.
Published On: January 28, 2020
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Application Type - Machine Learning | Compute - Intel® Xeon Scalable | Deployment Channel - CSP - Amazon Web Services, CSP - Google Cloud, CSP - Microsoft Azure, CSP - Other, On-premise (Private Cloud, Other) | Framework Optimizations - TensorFlow | Industry - Cross-Industry | Model Training - Models can be trained - requires labeled data | Offering Type - AI Software/SaaS | Operating System - Windows, Linux, Other (pls specify) | Software Libraries - Intel® Math Kernel Library (Intel® MKL), Intel® Data Analytics Acceleration Library (Intel® DAAL), Intel® Distribution for Python | Solution Geographic Availability - Worldwide | Use Case - Anomaly Detection, Other (pls specify), Predictive maintenance and analytics, Data Preparations and Management
This reference architecture outlines how combining H2O.ai products, 2nd generation Intel Xeon Scalable processors, and Intel DC SSDs can decrease training time and inference time without sacrificing model accuracy.
This document describes the components of RECAP, a novel integrated architecture and optimisation framework for optimising edge networks and distributed applications deployed on them. Models for understanding capacity provisioning for distributed edge networks are described, followed by a solution for intelligent and dynamic resource placement optimisation and orchestration. This is illustrated through a case study of an NFV-based LTE network. The results show how the proposed RECAP architecture can be used to optimise customer QoS and QoE while at the same time minimising infrastructure provider CAPEX and OPEX.
This document describes the components of RECAP, a novel integrated architecture and optimisation framework for optimising edge networks and distributed applications deployed on them. Models for understanding capacity provisioning for distributed edge networks are described, followed by a solution for intelligent and dynamic resource placement optimisation and orchestration. This is illustrated through a case study of an NFV-based LTE network. The results show how the proposed RECAP architecture can be used to optimise customer QoS and QoE while at the same time minimising infrastructure provider CAPEX and OPEX.
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