University of Arizona

Dataware Ventures, LLC

Teradata Us, Inc.

Rui Zhang

Hong Hua

Richard T Snodgrass

Saumya K Debray

Paul Laurence Sinclair

Sanjay Nair

Mamatha Govind Rao

Christian Convey

Yang Liu

A computer-implemented method and related systems for reducing memory access stalls and memory allocation requests in data-intensive applications are provided. Invariants associated with execution paths that access data in a memory of the data-intensive application are identified. At least one field specialization technique using at least one speccode segment is then applied. The speccode segment exploits the identified invariants, thereby reducing at least one of memory stalls and memory allocation requests in a data-intensive application. The field specialization technique may include specialized software prefetching, a data distribution-based hash function, process to CPU binding, memory segment reuse, or memory layout optimization, or any combination thereof.

Field specialization to reduce memory-access stalls and allocation requests in data-intensive applications

The present invention relates generally to a head-mounted projection display, and more particularly, but not exclusively to a polarized head-mounted projection display including a light engine and a compact, high-performance projection lens for use with reflective microdisplays.

Head-mounted projection display using reflective microdisplays

A system and method for loading data into column-partitioned database tables. The system and method incorporate a mechanism for buffering data extracted from the rows of a source table in column-oriented fashion within an in-buffer memory, enabling an efficient bulk-write of large arrays of values from the buffer into column-partitioned database tables. The system and method may also include optimizations for grouping columns according to data types and altering the order in which columns are inserted into the database tables.

Buffered data-loading in column-partitioned database tables

A method to minimize cache pressure using slot pressure profile (SPP)-guided Algorithm includes generating an intermediate SPP from a binary code of a DBMS. The generated intermediate SPP is received and a reference SPP is output. The reference SPP has a value assigned for each cache slot in a cache, whereby a cache slot value is indicative of cache pressure. The reference SPP is accepted and a candidate slot list related to the cache is produced by sorting the values in the reference SPP. A slot number among the candidate slot list is decided and passed to find an open memory address mapping to the decided slot number for a bee code, the bee code being a specialized version of a DBMS function created and loaded into the cache at run-time. A query with the bee code is executed using the open memory address found.

Broadening field specialization

Three extensions to the conventional field specialization process are disclosed. The first extension is cross-application value flows, where a value transfers out of one application and subsequently into another application. The second extension is an inter-application analysis. Static and dynamic analysis is performed by a Spiff Toolset not just on the source code of a single application, but also across the data read and written by that application. The third extension is invariant cross-application termination, verifying the possibility of an invariant originating in an application and terminating in a specialization opportunity in a separate application. An ecosystem specification is disclosed to enable such field specialization broadening. This specification states which applications are involved, what input data sources are read, what intermediate and final data products are produced, and what services are invoked, thereby providing valuable information on how intermediate results are communicated among the various applications.

Systems and methods for utilizing relation- and query-specific information to specialize DBMS code at runtime based on identifying runtime locally invariant variables. Runtime invariant is often of the form of variables in code that hold values that are constant during a portion of code execution. Micro-specialization is applied to eliminate from the original program unnecessary code such as branching statements that reference local invariant(s) in branch-condition evaluation. The resulting specialized code reduces the code complexity as well as significantly improves the runtime efficiency during code execution.

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Kirkland, WA, United States of America

Rui Zhang