Abstract: Methods for resolving a number of in-memory issues associated with parallel query execution of a database operation on a database utilizing a graphics processing unit (GPU) are presented including: tying a table choice to a number of accesses per second made to a table; and synchronizing threads in a same shared GPU multiprocessor to avoid compromising concurrency, and where the parallel query execution of the database operation is performed solely by the GPU. In some embodiments, methods further include storing data from the GPU to a disk to solve volatility; and enabling a user, at any time, to query the amount of memory being used by the table created by the user to monitor memory consumption.

Abstract: Methods for resolving a number of in-memory issues associated with parallel query execution of a database operation on a database utilizing a graphics processing unit (GPU) are presented including: tying a table choice to a number of accesses per second made to a table; and synchronizing threads in a same shared GPU multiprocessor to avoid compromising concurrency, and where the parallel query execution of the database operation is performed solely by the GPU. In some embodiments, methods further include storing data from the GPU to a disk to solve volatility; and enabling a user, at any time, to query the amount of memory being used by the table created by the user to monitor memory consumption.

Abstract: Methods for parallel query execution of a database operation on a database utilizing a graphics processing unit (GPU) are presented including: receiving query by a host, the query including database relations; starting a GPU kernel, where the GPU kernels include a GPU memory; hash partitioning the database relations by the GPU kernel; loading the partitioned database relations into the GPU memory; loading keyed partitions corresponding the hash partitioned database relations into the GPU memory; building a hash table for a smaller of the hash partitioned database relations; and executing the query. In some embodiments, methods further include returning a result of the query. In some embodiments, methods further include when the query is a long query including a number of operators, parsing the long query into a number of sub-queries; for each of the sub-queries, starting one of the GPU kernels such that the sub-queries are processed in parallel.

Abstract: Methods for parallel query execution of a database operation on a database utilizing a graphics processing unit (GPU) are presented including: receiving query by a host, the query including database relations; starting a GPU kernel, where the GPU kernels include a GPU memory; hash partitioning the database relations by the GPU kernel; loading the partitioned database relations into the GPU memory; loading keyed partitions corresponding the hash partitioned database relations into the GPU memory; building a hash table for a smaller of the hash partitioned database relations; and executing the query. In some embodiments, methods further include returning a result of the query. In some embodiments, methods further include when the query is a long query including a number of operators, parsing the long query into a number of sub-queries; for each of the sub-queries, starting one of the GPU kernels such that the sub-queries are processed in parallel.