Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.

Abstract: An online agricultural system manages and optimizes interactions of entities within the system to enable the execution of transaction and the transportation of crop products. The online agricultural system accesses historic and environmental data describing factors that may impact crop product transactions and/or transportation to determine market prices for crop products and crop product transportation. Responsive to receiving a request from an entity, the online agricultural system determines an optimal transaction for the entity, such as a price for selling a crop product, an available crop product for purchase, or a transportation opportunity to transport a crop product.

Abstract: A data deduplication method using a small hash digest dictionary in fast-access memory. The method includes receiving customer data, dividing the data into smaller chunks, and assigning hash values to each chunk. For each chunk, the method includes performing lookup for a duplicate chunk by accessing a small dictionary in memory with the chunk's hash value. When no entry, the small dictionary is updated to include the hash value to fill the dictionary with earliest received data. When an entry is found, the entry's hash value is compared with lookup value and if matched, reference data is returned and an entry counter is incremented. If not matched, additional accesses are attempted such as with additional indexes calculated using the hash value. Collisions may trigger an entry replacement such that some initially entered entries are replaced when determined to not be most repeating values such as based on their counter value.

Abstract: A data deduplication method using a small hash digest dictionary in fast-access memory. The method includes receiving customer data, dividing the data into smaller chunks, and assigning hash values to each chunk. For each chunk, the method includes performing lookup for a duplicate chunk by accessing a small dictionary in memory with the chunk's hash value. When no entry, the small dictionary is updated to include the hash value to fill the dictionary with earliest received data. When an entry is found, the entry's hash value is compared with lookup value and if matched, reference data is returned and an entry counter is incremented. If not matched, additional accesses are attempted such as with additional indexes calculated using the hash value. Collisions may trigger an entry replacement such that some initially entered entries are replaced when determined to not be most repeating values such as based on their counter value.

Abstract: The network attached virtual tape storage subsystem interconnects a plurality of tape devices with a plurality of data processors via a high bandwidth switching network to implement a virtual, distributed tape data storage subsystem. The virtual, distributed tape data storage system realizes multiple virtual devices, which are available to any of the data processors and the bandwidth of the system is scalable and can be changed on demand. The virtual tape storage subsystem is managed by a system controller which contains a plurality of software elements including: resource allocation, resource configuration, and resource management. The use of a networked storage manager enables the tape devices to be managed as a pool and yet attach the tape devices directly to the network as individual resources.