Patent Application Titled "Asynchronous Compute Integrated into Large-Scale Data Rendering Using Dedicated, Separate Computing and Rendering Clusters" Published Online
The assignee for this patent application is
Reporters obtained the following quote from the background information supplied by the inventors: "Typically, a large-scale data set may be based on raw data that has been collected but has not undergone any form of processing. The large-scale raw data may be multiple times larger than a corresponding reduced data set. For instance, a factor of about 600 is not uncommon in the area of seismic data interpretation. That is, if a rendering system visualizes 200 GB of seismic volume data, then respective raw data could be approximately 120 TB in size. Usually, this large-scale raw data has to be preprocessed, which may require hours or even days, in order to provide a reduced data set that is capable of being further processed or manipulated for analysis in a user-interactive environment. In another aspect, preprocessing of the large-scale data set may incur unwanted (or unknown) filtering effects on the reduced data set, which in turn may provide misleading results during further analysis."
In addition to obtaining background information on this patent application, VerticalNews editors also obtained the inventors' summary information for this patent application: "Embodiments of the present disclosure provide an asynchronous computing and rendering system and an asynchronous computing and rendering method.
"In one embodiment, the asynchronous computing and rendering system includes a data storage unit that provides storage for processing a large-scale data set organized in accordance to data subregions and a computing cluster containing a parallel plurality of asynchronous computing machines that provide compute results based on the data subregions. The asynchronous computing and rendering system also includes a rendering cluster containing a parallel multiplicity of asynchronous rendering machines coupled to the asynchronous computing machines, wherein each rendering machine renders a subset of the data subregions. Additionally, the asynchronous computing and rendering system includes a data interpretation platform coupled to the asynchronous rendering machines that provides user interaction and rendered viewing capabilities for the large-scale data set.
"In another aspect, the asynchronous computing and rendering method includes providing data storage for processing a large-scale data set organized in accordance to data subregions and initiating asynchronous and parallel rendering, wherein each rendering corresponds to a subset of the data subregions. The method also includes instigating asynchronous and parallel computing having compute results based on the subset of the data subregions and providing user interaction and rendered viewing capabilities for the large-scale data set.
"The foregoing has outlined preferred and alternative features of the present disclosure so that those skilled in the art may better understand the detailed description of the disclosure that follows. Additional features of the disclosure will be described hereinafter that form the subject of the claims of the disclosure. Those skilled in the art will appreciate that they can readily use the disclosed conception and specific embodiment as a basis for designing or modifying other structures for carrying out the same purposes of the present disclosure.
"Reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:
"FIG. 1 illustrates a functional block diagram of an embodiment of an asynchronous computing and rendering system constructed according to the principles of the present disclosure;
"FIG. 2 illustrates an embodiment of an asynchronous computing and rendering system corresponding to the functional block diagram of FIG. 1;
"FIG. 3 illustrates a functional diagram that corresponds to one of the multiplicity of rendering machines of FIG. 1;
"FIG. 4 illustrates an example of hierarchical data decomposition as may be applied to a large-scale data set;
"FIGS. 5A and 5B illustrate an example of a scalable performance curve and a composited result for an asynchronous computing and rendering system constructed according to the principles of the present disclosure; and
"FIG. 6 illustrates an embodiment of an asynchronous computing and rendering method carried out according to the principles of the present disclosure."
For more information, see this patent application: Nienhaus, Marc; Mensmann, Joerg;
Keywords for this news article include:
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