Global World 3D Rendering And Virtualization Software Market Size, Sales, Share, Analysis, Industry Demand and Forecasts Report From 2019-2025

Amazingherald | May 09, 2019

Global World 3D Rendering And Virtualization Software Market Size, Sales, Share, Analysis, Industry Demand and Forecasts Report From 2019-2025
The Global World 3D Rendering And Virtualization Software Market research report provides an overview of the current market Trend, incremental revenue, and future outlook of the Global World 3D Rendering And Virtualization Softwaremarket. 3D rendering is the 3D computer graphics proce of automatically converting 3D wire frame models into 2D images with 3D photorealistic effects or non-photorealistic rendering on a computer.In computing, virtualization refers to the act of creating a virtual (rather than actual) version of something, including (but not limited to) a virtual computer hardware platform, operating system (OS), storage device, or computer network resources.

Spotlight

Public sector and federal government agencies are looking for better vehicles to tame IT budgets, and at the same time provide agile IT services to organizations, citizens and constituents. The paradigm of cloud computing, which has been recently introduced and developed, offers means for public managers and government executives to address issues of budget constraints and agility of service. Simultaneously, new cloud computing-based business models and vehicles are being debated, defined, and implemented in the industry. If adopted and implemented, these business models would require not only new architectures, but also new ways to acquire and procure IT services. These requirements imply that governments need to carefully evaluate how to adopt cloud computing.

Related News

Run:AI Creates First Fractional GPU That Effectively Creates Virtualized Logical GPUs

Run:AI | May 07, 2020

Run:AI's fractional GPU system effectively creates virtualized logical GPUs, with their own memory and computing space that containers can use and access as if they were self-contained processors. Run:AI also solved the problem of memory isolation, so each virtual GPU can run securely without memory clashes. The addition of fractional GPU sharing is a key component in Run:AI's mission to create a true virtualized AI infrastructure, combining. Run:AI, a company virtualizing AI infrastructure, today released the first fractional GPU sharing system for deep learning workloads on Kubernetes. Especially suited for lightweight AI tasks at scale such as inference, the fractional GPU system transparently gives data science and AI engineering teams the ability to run multiple workloads simultaneously on a single GPU, enabling companies to run more workloads such as computer vision, voice recognition and natural language processing on the same hardware, lowering costs. Today's de facto standard for deep learning workloads is to run them in containers orchestrated by Kubernetes. However, Kubernetes is only able to allocate whole physical GPUs to containers, lacking the isolation and virtualization capabilities needed to allow GPU resources to be shared without memory overflows or processing clashes. Read More: IT Management Solution Announces Updated Range of Virtualization Services for Businesses Run:AI's fractional GPU system effectively creates virtualized logical GPUs, with their own memory and computing space that containers can use and access as if they were self-contained processors. This enables several deep learning workloads to run in containers side-by-side on the same GPU without interfering with each other. The solution is transparent, simple and portable; it requires no changes to the containers themselves. To create the fractional GPUs, Run:AI had to modify how Kubernetes handled them. "In Kubernetes, a GPU is handled as an integer. You either have one or you don't. We had to turn GPUs into floats, allowing for fractions of GPUs to be assigned to containers. Run:AI also solved the problem of memory isolation, so each virtual GPU can run securely without memory clashes, Dr. Ronen Dar, co-founder and CTO of Run:AI. A typical use-case could see 2-4 jobs running on the same GPU, meaning companies could do four times the work with the same hardware. For some lightweight workloads, such as inference, more than 8 jobs running in containers can comfortably share the same physical chip. The addition of fractional GPU sharing is a key component in Run:AI's mission to create a true virtualized AI infrastructure, combining with Run:AI's existing technology that elastically stretches workloads over multiple GPUs and enables resource pooling and sharing. Some tasks, such as inference tasks, often don't need a whole GPU, but all those unused processor cycles and RAM go to waste because containers don't know how to take only part of a resource. Run:AI's fractional GPU system lets companies unleash the full capacity of their hardware so they can scale up their deep learning more quickly and efficiently, Run:AI co-founder and CEO Omri Geller. Read More: Synamedia Advances Video Network Portfolio with HPE ProLiant Servers for Network Virtualization About Run:AI Run:AI has built the world's first virtualization layer for AI workloads. By abstracting workloads from underlying infrastructure, Run:AI creates a shared pool of resources that can be dynamically provisioned, enabling full utilization of expensive GPU compute. IT teams retain control and gain real-time visibility – including seeing and provisioning run-time, queueing and GPU utilization – from a single web-based UI. This virtual pool of resources enables IT leaders to view and allocate compute resources across multiple sites - whether on premises or in the cloud. The Run:AI platform is built on top of Kubernetes, enabling simple integration with existing IT and data science workflows.

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SERVER VIRTUALIZATION

Samsung and TPG Telecom will Test Australia’s First 5G vRAN with an Integrated 26GHz mmWave Solution

Samsung | July 09, 2021

Today, Samsung Electronics said it would collaborate with TPG Telecom to undertake Australia's first 5G virtualized RAN (vRAN) trial on 26GHz, utilizing an integrated mmWave solution for mobile and fixed wireless services. Samsung will put its vRAN solution at TPG Telecom's brand new Innovation Lab in Glebe, NSW, for the trial, the first type in the country. Furthermore, Samsung's newest 5G mmWave product, Compact Macro, will be implemented in the Glebe region. The announcement follows the April 2021 launch of Samsung's Networks Business in Australia. The firm has been exploring the delivery of Samsung's leading 5G mmWave technology to the country since then. TPG Telecom, a major mobile network provider in Australia, owns and runs a number of well-known mobile and internet brands in the country, including Vodafone. TPG Telecom has announced a AU$108 million commitment to buy spectrum in all accessible license areas in the 26GHz band, doubling its overall spectrum holdings. TPG Telecom will provide high-speed data services and immersive use cases to its mobile and home customers because of an abundance of mmWave spectrum. In addition, TPG Telecom's extensive fiber assets, coupled with a small cell network, will allow for the deployment of vRAN architecture. Samsung will offer its Compact Macro and vRAN solutions for the trial. Samsung's newest 5G Compact Macro combines a baseband, radio, and antenna in a compact package. This compact and lightweight technology is easily placed on the sides of buildings and utility poles, allowing for the quick response of 5G networks. Samsung's industry-leading commercial vRAN solution is based on the company's own stack and operates on commercial-off-the-shelf (COTS) servers. As a vRAN leader, Samsung has commercially deployed its vRAN solution on a large scale for global Tier 1 operator networks in markets other than Australia and has recently expanded its capability to support the 3.5GHz Massive MIMO radio industry voices had predicted would be difficult to support with vRAN. Furthermore, Samsung's 5G vRAN on mmWave, which is currently commercially deployed in global markets such as Korea, Japan, and the United States, can handle multi-gigabit speeds, enabling IT technology savings and deployment benefits providing revolutionary 5G mobile experiences. Samsung has paved the way for successfully delivering 5G end-to-end solutions, including chipsets, radios, and core. With its market-leading product portfolio spanning from completely virtualized RAN and Core to private network solutions and AI-powered automation tools, Samsung leads the industry's advancement of 5G networks through ongoing research and development. Currently, the company provides network solutions to mobile operators that connect hundreds of millions of users worldwide. About TPG Telecom TPG Telecom is an Australian telecommunications company that owns some of the country's most recognizable brands, including Vodafone, TPG, iiNet, AAPT, Internode, Lebara, and Felix. TPG Telecom owns and operates national mobile and fixed networks that improve Australia's connectivity. These include Australia's second-largest fixed voice and data network, with over 27,000 kilometers of metropolitan and inter-capital fiber networks, and a leading mobile network with over 5,600 sites and a population of over 23 million Australians. TPG Telecom, ASX's second-biggest telecoms business, has a strong challenger spirit and a dedication to providing the best services and solutions to our customers.

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HYPER-V

Virtana Expands Monitoring Coverage and Enhances Infrastructure Capacity Planning with Latest Version of VirtualWisdom

Virtana | November 16, 2021

Virtana, the leader in hybrid infrastructure management for mission-critical workloads, introduced the latest version of VirtualWisdom, the premier hybrid IT infrastructure management and AIOps platform for mission-critical workloads. VirtualWisdom 6.3 is the first product launch since Virtana’s rebrand in October 2019 and continues the company’s push into capacity management with global storage array analytics, an expanded range of integrations, and new portable reports and dashboards. Mission-critical hybrid applications combine resources in public clouds, with physical or virtual resources residing in private data centers. For these crucially important workloads, operating at web-scale, managing cost, performance, and capacity has never been more complex or important. To gain the insights and operational control that deliver efficient, cost-effective operation, organizations need real-time visibility, automated discovery, AI-powered analytics, and immediate access to best-practice solutions that proactively solve infrastructure-related performance and capacity issues for critical applications. VirtualWisdom provides real-time, data-driven lifecycle recommendations to assure performance, speed problem resolution, automate workload optimization, free-up capacity, and ensure resource availability. AI-powered capacity forecasting helps organizations avoid capacity-driven problems before they can happen, and AI-powered workload optimization keeps applications operating within SLAs. “To provide organizations with a competitive advantage, IT needs to use and manage their resources efficiently. IT professionals need tools to enable them to quickly resolve problems, even as the infrastructure becomes increasingly more complex. They also need to automate as many of the mundane IT tasks as possible,” said George Crump, President and Founder of Storage Switzerland. “Powered by AI/ML capabilities, VirtualWisdom offers recommendations and automated problem resolution, providing customers with deep infrastructure visibility.” The new VirtualWisdom release features the new Capacity Auditor, a global storage array analytic that offers a unique approach to global capacity management designed to provide app-centric insights and intelligence across hybrid infrastructure and multi-vendor data storage environments. With Capacity Auditor, organizations have a broad view of storage usage and trends across all storage arrays, applications, locations, physical storage assets, and effective capacity. Other key features of the new VirtualWisdom 6.3 release include: New infrastructure integrations: Support for Oracle’s Solaris, Red Hat KVM, and Pure Storage solutions that provide all the power of the VirtualWisdom platform to applications using infrastructure within these environments, and management of infrastructure elements that live within them. Dynamic entity insights: Enhances VirtualWisdom’s continuous real-time infrastructure discovery with simple, intuitive dashboards and reports for servers, storage, and networks. Enabling immediate insights into critical relationships between infrastructure elements, visibility into vital statistics, and the capability to automatically apply customizable information sets for identification and cost. Portable reports: Empowers users to share collective insights, dashboards and reports across the VirtualWisdom community. Customers and partners can easily exchange best-practice monitoring reports and visualizations unique to specific environments and applications. Hybrid Application Definition: Hybrid, real-time application views make it easy to visualize hybrid applications that cross multiple technology boundaries in one view – including applications that span multiple clouds (AWS, Azure), virtual environments (VMware, KVM, HyperV, PowerVM) as well as physical systems. “The Virtana VirtualWisdom platform has been a fundamental enabler of our mission-critical manufacturing technology solutions and services for many years now,” said Todd Weeks, Plex Systems Global VP of Cloud Operations. “Our ability to offer our customers nearly 100% business continuity in a highly efficient cloud infrastructure relies on the real-time infrastructure visibility and AI-powered analytics that are unique to the VirtualWisdom platform.” “Digital transformation is driving exponential data growth as today’s enterprises must have global visibility into all storage resources to continuously meet these ever-growing demands. Point solutions to managing data sets across multiple vendor storage environments result in highly fragmented, manual and wasteful practices and resources – and can put entire applications at risk. With application aware, predictive insight into the underlying digital infrastructure, VirtualWisdom offers the industry’s first and only global infrastructure capacity auditor and forecaster that can providing real-time visibility into mission-critical digital workload infrastructure.” Tim Van Ash, SVP of Products at Virtana The latest version of VirtualWisdom is currently being showcased at the Gartner Infrastructure Operations and Cloud Summit in Las Vegas. Todd Weeks, Plex Systems Global VP of Cloud Operations will be speaking on Dec. 11 at 11:15 a.m. on “How Virtana Empowers Peak Performance for the Plex Manufacturing Cloud.” About Virtana Virtana is a leader in hybrid infrastructure management for mission-critical workloads, providing comprehensive hybrid IT infrastructure monitoring and real-time, AI-powered analytics for the modern enterprise data center. The company’s solutions give IT operations teams’ deep workload visibility and actionable insights into their end-to-end systems that support mission-critical applications. Virtana customers include leaders in enterprise IT, cloud service providers and federal agencies that are leveraging the company’s platforms to maximize the performance, health and utilization of their hybrid IT infrastructure. The privately-held company is headquartered in San Jose, Calif.

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Spotlight

Public sector and federal government agencies are looking for better vehicles to tame IT budgets, and at the same time provide agile IT services to organizations, citizens and constituents. The paradigm of cloud computing, which has been recently introduced and developed, offers means for public managers and government executives to address issues of budget constraints and agility of service. Simultaneously, new cloud computing-based business models and vehicles are being debated, defined, and implemented in the industry. If adopted and implemented, these business models would require not only new architectures, but also new ways to acquire and procure IT services. These requirements imply that governments need to carefully evaluate how to adopt cloud computing.