SYSTEM AND METHOD FOR AUTHORING HIGH QUALITY RENDERINGS AND GENERATING MANUFACTURING OUTPUT OF CUSTOM PRODUCTS

1 . A data flow network configured to process data in parallel, the data flow network comprising:

a plurality of data processing modules implemented in a data flow network and configured to process, in parallel, input data and to generate output data;

wherein a specific class of data processing module of the plurality of data processing modules is configured to receive data of the input data and/or the output data of other modules;

evaluate the data to determine a type of processing for the data;

generate, based on the type of processing for the data, the result data of the output data; and transmit the result data to one or more of the plurality of data processing modules;

wherein processing the data, by the specific class of data processing module of the plurality of data processing modules, comprises controlling a flow of the data based on one or more controlling functionalities implemented in the data processing module;

wherein processing the data, by the specific class of data processing module of the plurality of data processing modules, comprises routing result data to the one or more of the plurality of data processing modules according to the flow of the data.

2 . The data flow network of claim 1 , wherein the data processing module of the plurality of data processing modules is further configured to: determine a probability value by the data processing module;

wherein the probability value indicates a likelihood of success of the processing of the data by the data processing module;

wherein the probability value indicates the likelihood of success that the processing of the data by the data processing module succeeded.

3 . The data flow network of claim 2 , wherein the data processing module of the plurality of data processing modules is further configured to: determine whether the probability value that indicates the likelihood of success that the processing of the data by the data processing module exceeds a threshold value;

in response to determining that the probability value exceeds the threshold value, determine that the processing of the data has succeeded, and transmit the result data to the one or more of the plurality of data processing modules to indicate a success state of data processing by the data processing module.

4 . The data flow network of claim 3 , wherein the data processing module of the plurality of data processing modules is further configured to:

in response to determining that the probability value does not exceed the threshold value, determine that the processing of the data has failed, and transmit the result data to the one or more of the plurality of data processing modules to indicate a failed state of data processing by the data processing module.

5 . The data flow network of claim 2 , wherein the probability value indicating the success is determined by executing the one or more controlling functionalities implemented in the data processing module.

6 . The data flow network of claim 1 , wherein the processing of the data by the data processing module includes one or more of:

determining whether a particular layer definition is present in the data,

selecting, based on one or more criteria, a particular data processing module, of the one or more data processing modules, for transmitting the result data from the data processing model, or

processing a plurality of key-value pairs included in the data.

7 . The data flow network of claim 1 , wherein the one or more data processing modules of the plurality of data processing modules execute as one or more parallel threads;

wherein execution of the one or more parallel threads is optimized according to one or more optimization criteria selected based on one or more of: types of the input data, the plurality of data processing modules, or types of the output data.

8 . A data flow processing method for processing data in parallel, the method comprising:

processing, in parallel, input data to generate output data by a plurality of data processing modules implemented in a data flow network;

wherein a specific class of data processing module of the plurality of data processing modules is configured to receive data of the input data and/or the output data;

evaluate the data to determine a type of processing for the data;

generate, based on the type of processing for the data, result data of the output data; and transmit the result data to one or more of the plurality of data processing modules;

wherein processing the data, by the specific class of data processing module of the plurality of data processing modules, comprises controlling a flow of the data based on one or more controlling functionalities implemented in the data processing module;

wherein processing the data, by the specific class of data processing module of the plurality of data processing modules, comprises routing result data to the one or more of the plurality of data processing modules according to the flow of the data.

9 . The data flow processing method of claim 8 , wherein the data processing module of the plurality of data processing modules is further configured to: determine a probability value by the data processing module;

wherein the probability value indicates a likelihood of success of the processing of the data by the data processing module;

wherein the probability value indicates the likelihood of success that the processing of the data by the data processing module succeeded.

10 . The data flow processing method of claim 9 , wherein the data processing module of the plurality of data processing modules is further configured to: determine whether the probability value that indicates the likelihood of success that the processing of the data by the data processing module exceeds a threshold value;

in response to determining that the probability value exceeds the threshold value, determine that the processing of the data has succeeded, and transmit the result data to the one or more of the plurality of data processing modules to indicate a success state of data processing by the data processing module.

11 . The data flow processing method of claim 10 , wherein the data processing module of the plurality of data processing modules is further configured to:

in response to determining that the probability value does not exceed the threshold value, determine that the processing of the data has failed, and transmit the result data to the one or more of the plurality of data processing modules to indicate a failed state of data processing by the data processing module.

12 . The data flow processing method of claim 9 , wherein the probability value indicating the success is determined by executing the one or more controlling functionalities implemented in the data processing module.

13 . The data flow processing method of claim 9 , wherein the processing of the data by the data processing module includes one or more of:

determining whether a particular layer definition is present in the data,

selecting, based on one or more criteria, a particular data processing module, of the one or more data processing modules, for transmitting the result data from the data processing model, or

processing a plurality of key-value pairs included in the data.

14 . The data flow processing method of claim 8 , wherein the one or more data processing modules of the plurality of data processing modules execute as one or more parallel threads;

wherein execution of the one or more parallel threads is optimized according to one or more optimization criteria selected based on one or more of: types of the input data, the plurality of data processing modules, or types of the output data.