Abstract: Methods and systems are described for applying the use of shards within a single memory address space. A database request is processed by providing the request from a client to a processor, the processor then distributing the request to multiple threads within a single process but executing in a shared memory address environment, wherein each thread performs the request on a distinct shard, and aggregating the results of the multiple threads being aggregated and returning a final result to the client. By parallelizing operations in this way, the request response time can be reduced and the total amount of communication overhead can be reduced.

Abstract: As described herein, a database machine is provided with specialized hardware that can be used to accelerate the sort function. This hardware lowers the computation cost of performing a raw sort operation over the result rows. The hardware may be embodied in a direct circuit (e.g., ASIC), a programmable circuit (e.g., FPGA), a parallel compute engine (e.g., GPU) or any parallel computer. A hardware-assisted sort procedure provides for the early return of up to K results. This early return feature is critically valuable in database operations because often an entire result set is not required. For requests that require only the first L results, when L<=K the query can be satisfied with only a single pass over the data. The hardware- or GPU-assisted sort procedure, referred to herein as “scraper sort,” may be based on modifications of well-known, existing parallel sort algorithms.

Abstract: Load balancing in a parallel database system is performed using multi-reordering, in which a sequence of multiple processors (two, three, or more) that have small average load (for example, the smallest of any such sequence) is selected to participate in load balancing. In the case of three adjacent low-load processors, the load of all three is evenly distributed over two of them, and the remaining processor becomes a free processor. The free processor is moved adjacent to a high-load processor, the load of which is then shared with the free processor. Data is moved in a “transaction” so that the view of data is always consistent. The database continues to service requests from a former location while data undergoes a transfer.

Abstract: Load balancing in a parallel database system is performed using multi-reordering, in which a sequence of multiple processors (two, three, or more) that have small average load (for example, the smallest of any such sequence) is selected to participate in load balancing. In the case of three adjacent low-load processors, the load of all three is evenly distributed over two of them, and the remaining processor becomes a free processor. The free processor is moved adjacent to a high-load processor, the load of which is then shared with the free processor. Data is moved in a “transaction” so that the view of data is always consistent. The database continues to service requests from a former location while data undergoes a transfer.

Abstract: As described herein, a database machine is provided with specialized hardware that can be used to accelerate the sort function. This hardware lowers the computation cost of performing a raw sort operation over the result rows. The hardware may be embodied in a direct circuit (e.g., ASIC), a programmable circuit (e.g., FPGA), a parallel compute engine (e.g., GPU) or any parallel computer. A hardware-assisted sort procedure provides for the early return of up to K results. This early return feature is critically valuable in database operations because often an entire result set is not required. For requests that require only the first L results, when L<=K the query can be satisfied with only a single pass over the data. The hardware- or GPU-assisted sort procedure, referred to herein as “scraper sort,” may be based on modifications of well-known, existing parallel sort algorithms.

Abstract: Load balancing in a parallel database system is performed using multi-reordering, in which a sequence of multiple processors (two, three, or more) that have small average load (for example, the smallest of any such sequence) is selected to participate in load balancing. In the case of three adjacent low-load processors, the load of all three is evenly distributed over two of them, and the remaining processor becomes a free processor. The free processor is moved adjacent to a high-load processor, the load of which is then shared with the free processor. Data is moved in a “transaction” so that the view of data is always consistent. The database continues to service requests from a former location while data undergoes a transfer.

Abstract: Methods and systems are described for applying the use of shards within a single memory address space. A database request is processed by providing the request from a client to a processor, the processor then distributing the request to multiple threads within a single process but executing in a shared memory address environment, wherein each thread performs the request on a distinct shard, and aggregating the results of the multiple threads being aggregated and returning a final result to the client. By parallelizing operations in this way, the request response time can be reduced and the total amount of communication overhead can be reduced.

Abstract: A vertical axis wind turbine has one or more blades (10) mounted in cantilever manner on a hub (12) on a short tower (14). The or each blade (10) is unsupported above the level of the hub (12) and extends freely upwards. The hub (12) may be a rigid mounting or a pivot mounting. If two blades (10) are used, they are desirably arranged in a crossed configuration so as to extend along a common axis. The upward arm of the blade (10) can be straight and rigid, or flexible, or cranked, or curved. The wind turbine is suitable both for land-based use and on water-going craft.