IBM Files Patent For GPU-Accelerated Databases

Instead of traditional disk-based queries and an approach that slows performance via memory latencies and processors waiting for data to be fetched from the memory, IBM envisions in-GPU-memory tables as technology that could, in addition to disk tables, significantly accelerate database processing. According to a patent filed by the company, "GPU enabled programs are well suited to problems that involve data-parallel computations where the same program is executed on different data with high arithmetic intensity."

However, IBM is not surprisingly trying to protect its patent, if granted, in other programming languages as in the key areas of:

- starting a GPU kernel
- 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
- executing the query.

According to the patent applications, using GPU acceleration for databases "may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages." To cover all of its bases, IBM also states that the "program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server."

Wolfgang Gruener
Contributor

Wolfgang Gruener is an experienced professional in digital strategy and content, specializing in web strategy, content architecture, user experience, and applying AI in content operations within the insurtech industry. His previous roles include Director, Digital Strategy and Content Experience at American Eagle, Managing Editor at TG Daily, and contributing to publications like Tom's Guide and Tom's Hardware.