November 17, 2011
Nov. 17 — NICE is pleased to announce the immediate availability of the 2012.0 release of its Desktop Cloud Visualization (NICE DCV) product. This new release represents a breakthrough in remote 3D visualization, as it is the first product in the market to perform GPU sharing across multiple Microsoft Windows and Linux Desktops.
Extending existing support for Linux and Windows running on physical nodes, NICE DCV is now bringing full GPU acceleration to virtual machines, therefore enabling companies and cloud providers to deliver Virtual Workstations services to their users.
Therefore, the new version of NICE DCV allows multiple users to run OpenGL applications served by a private or public cloud configuration, or just simply remotely access their own dedicated workstation sitting in their office or datacenter, via LAN or WAN.
Leveraging partnerships with leading technology providers and OEMs, NICE DCV has been tuned to get the best performance on NVIDIA high-end Quadro and Tesla GPUs running major CAD applications, as well as many Technical Computing applications.
When NICE DCV is complemented with our flagship EnginFrame HPC and Remote Visualization gateway, customers can enjoy Web-based access to the most demanding batch and interactive applications, boosting data access performance, model scalability and overall user productivity compared to traditional desk-side based computing.
To learn more:
NICE delivers comprehensive grid & technical computing cloud products and solutions. NICE product portfolio boosts productivity of private and public clouds by increasing usability and user-friendliness, without sacrificing flexibility and control. NICE global customers include leading companies in automotive, aerospace, industry manufacturing, oil & gas, life science, universities and scientific research.
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When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
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