Abstract: An instruction processing apparatus is disclosed. The instruction processing apparatus includes: a selector is configured to parse out a command type and a buffer identifier from a command, provide received data and the buffer identifier to a parser if the command type is configuration, and provide the received data and the buffer identifier to an operation circuit if the command type is execution; the parser is configured to parse out an instruction sequence from the data, store the instruction sequence into an instruction buffer corresponding to the buffer identifier, and store an operand of each instruction into a register file; and the operation circuit is configured to drive the instruction buffer to execute each instruction and generate a control signal, and trigger a plurality of execution units to perform operations based on received control signals and operands. The apparatus may be dedicated to processing various neural network applications.

Abstract: Disclosed herein is Arrowland, a web-based software tool for inputting, managing and viewing multiomics data, such as transcriptomics, proteomics, metabolomics and fluxomics data in an interactive, intuitive and multiscale system.

Abstract: An instruction processing apparatus is disclosed. The instruction processing apparatus includes: a selector is configured to parse out a command type and a buffer identifier from a command, provide received data and the buffer identifier to a parser if the command type is configuration, and provide the received data and the buffer identifier to an operation circuit if the command type is execution; the parser is configured to parse out an instruction sequence from the data, store the instruction sequence into an instruction buffer corresponding to the buffer identifier, and store an operand of each instruction into a register file; and the operation circuit is configured to drive the instruction buffer to execute each instruction and generate a control signal, and trigger a plurality of execution units to perform operations based on received control signals and operands. The apparatus may be dedicated to processing various neural network applications.

Abstract: Disclosed are an acceleration unit for executing a neural network model and a server. The acceleration unit includes: a plurality of cluster groups, where each of the cluster groups includes a plurality of processing clusters; an on-chip memory, including a plurality of storage units, where each storage unit corresponds to each of the cluster groups, and is configured to store an instruction sequence and operation data of the corresponding cluster group; a command processor, configured to decompose an operation associated with a specified neural network model into a plurality of sub-operations, convert the plurality of sub-operations into a plurality of instruction sequences, specify operation data of each of the instruction sequences; and a plurality of distribution units, where each distribution unit reads the instruction sequence and operation data of the instruction sequence from the corresponding storage unit into the corresponding cluster group.

Abstract: The present disclosure provides a method and device for predicting a production performance of an oil reservoir. The method includes: determining a single-well numerical simulation data set according to geological parameters, rock and fluid parameters and construction data; performing reservoir numerical simulation based on the single-well numerical simulation data set, and determining a standard data set for oil reservoir production performance prediction; establishing a deep belief network (DBN) model for oil reservoir production performance prediction according to the standard data set; and predicting the production performance of a target well by using the DBN model to obtain a production performance prediction result of the target well. The present disclosure can be used to fast and accurately predict the production performance of an oil well in an unconventional oil reservoir. For a given block, the DBN model can be used indefinitely without the target well being put into production.

Abstract: Disclosed herein is Arrowland, a web-based software tool for inputting, managing and viewing multiomics data, such as transcriptomics, proteomics, metabolomics and fluxomics data in an interactive, intuitive and multiscale system.

Abstract: A method of measuring contamination in fluid that is expelled from a food processing system is presented. The method of measuring is carried out with fluorescence. The fluid is typically allowed to enter into an energy transfer system, but if the contamination exceeds a certain level, the fluid should be prevented from entering the energy transfer system. The fluid is generally comprised of water expelled from a sugar processing operation.

Abstract: The invention provides devices, methods, and compositions for dry chemical reagents to measure calcium, magnesium (total hardness), and other analytes in water using colorimetric devices. The measurement may be a one-step procedure without the need of dilution and multi-step preparation, so that it can be easily employed by untrained personnel. The chemical reagents may include dyes, buffer reagents, masking reagents, competing ligands, and other chemicals such as fillers. The chemical reagents may be grinded together as a homogenous fine powder, equally dispensed into small containers for each test or dried as film or solid using the means of air, low heat or vacuum. The composition may be easily dissolved into water samples and stable for long term storage.

Abstract: A method of measuring contamination in fluid that is expelled from a food processing system is presented. The method of measuring is carried out with fluorescence. The fluid is typically allowed to enter into an energy transfer system, but if the contamination exceeds a certain level, the fluid should be prevented from entering the energy transfer system. The fluid is generally comprised of water expelled from a sugar processing operation.