Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.

Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.

Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.

Abstract: For one embodiment of the present invention, methods and systems for accelerating data operations with efficient memory management in native code and native dynamic class loading mechanisms are disclosed. In one embodiment, a data processing system comprises memory and a processing unit coupled to the memory. The processing unit is configured to receive input data, to execute a domain specific language (DSL) for a DSL operation with a native implementation, to translate a user defined function (UDF) into the native implementation by translating user defined managed software code into native software code, to execute the native software code in the native implementation, and to utilize a native memory management mechanism for the memory to manage object instances in the native implementation.

Abstract: Methods and systems are disclosed for accelerating Big Data operations by utilizing subgraph templates for a hardware accelerator of a computational storage device. In one example, a computer-implemented method comprises performing a query with a dataflow compiler, performing a stage acceleration analyzer function including executing a matching algorithm to determine similarities between sub-graphs of an application program and unique templates from an available library of templates; and selecting at least one template that at least partially matches the sub-graphs with the at least one template being associated with a linear set of operators to be executed sequentially within a stage of the Big Data operations.

Abstract: For one embodiment of the present invention, methods and systems for accelerating data operations with efficient memory management in native code and native dynamic class loading mechanisms are disclosed. In one embodiment, a data processing system comprises memory and a processing unit coupled to the memory. The processing unit is configured to receive input data, to execute a domain specific language (DSL) for a DSL operation with a native implementation, to translate a user defined function (UDF) into the native implementation by translating user defined managed software code into native software code, to execute the native software code in the native implementation, and to utilize a native memory management mechanism for the memory to manage object instances in the native implementation.

Abstract: A diagnostic apparatus monitors a lithographic manufacturing system. First measurement data representing local deviations of some characteristic across a substrate is obtained using sensors within a lithographic apparatus, and/or a separate metrology tool. Other inspection tools perform substrate backside inspection to produce second measurement data. A high-resolution backside defect image is processed into a form in which it can be compared with lower resolution information from the first measurement data. Cross-correlation is performed to identify which of the observed defects are correlated spatially with the deviations represented in the first measurement data. A correlation map is used to identify potentially relevant clusters of defects in the more detailed original defect map. The responsible apparatus can be identified by pattern recognition as part of an automated root cause analysis. Alternatively, reticle inspection data may be used as second measurement data.

Abstract: Methods and systems are disclosed for a cache architecture for accelerating operations of a column-oriented database management system. In one example, a hardware accelerator for data stored in columnar storage format comprises at least one decoder to generate decoded data, a cache controller coupled to the at least one decoder. The cache controller comprising a store unit to store data in columnar format, cache admission policy hardware for admitting data into the store unit including a next address while a current address is being processed, and a prefetch unit for prefetching data from memory when a cache miss occurs.

Abstract: Methods and systems are disclosed for accelerating big data operations by utilizing subgraph templates. In one example, a data processing system includes a data processing system comprising a hardware processor and a hardware accelerator coupled to the hardware processor. The hardware accelerator is configured with a compiler of an accelerator functionality to generate an execution plan, to generate computations for nodes including subgraphs in a distributed system for an application program based on the execution plan, and to execute a matching algorithm to determine similarities between the subgraphs and unique templates from an available library of templates.

Abstract: A diagnostic apparatus monitors a lithographic manufacturing system. First measurement data representing local deviations of some characteristic across a substrate is obtained using sensors within a lithographic apparatus, and/or a separate metrology tool. Other inspection tools perform substrate backside inspection to produce second measurement data. A high- resolution backside defect image is processed into a form in which it can be compared with lower resolution information from the first measurement data. Cross-correlation is performed to identify which of the observed defects are correlated spatially with the deviations represented in the first measurement data. A correlation map is used to identify potentially relevant clusters of defects in the more detailed original defect map. The responsible apparatus can be identified by pattern recognition as part of an automated root cause analysis. Alternatively, reticle inspection data may be used as second measurement data.

Abstract: A diagnostic apparatus monitors a lithographic manufacturing system. First measurement data representing local deviations of some characteristic across a substrate is obtained using sensors within a lithographic apparatus, and/or a separate metrology tool. Other inspection tools perform substrate backside inspection to produce second measurement data. A high-resolution backside defect image is processed into a form in which it can be compared with lower resolution information from the first measurement data. Cross-correlation is performed to identify which of the observed defects are correlated spatially with the deviations represented in the first measurement data. A correlation map is used to identify potentially relevant clusters of defects in the more detailed original defect map. The responsible apparatus can be identified by pattern recognition as part of an automated root cause analysis. Alternatively, reticle inspection data may be used as second measurement data.

Abstract: A vibratory feeder, conveyor, separator, screen, or other vibratory equipment used in materials handling and related fields of the tuned two mass type in which one mass is an imbalance generator of the type using eccentric weights on a rotating shaft uses helical coil springs for coupling the imbalance generator to the trough or the like without clamping of the ends of the springs or constraining them to remain parallel to each other. Decoupling of the lateral oscillatory forces from the trough is achieved by using at least two pairs of collinear springs, one of each pair on each side of a wall member secured to the trough, and each held in compression between the wall member and a pair of vibrator plates held in fixed spaced apart relationship on each side of the wall member. The imbalance generator is secured to one of the vibrator plates so as to be well outside the spring system thus giving a low natural lateral frequency to the two mass system.