Battelle Memorial Institute

Nvidia Corporation

Oreste Villa

Antonino Tumeo

David J Haglin

Jesse R Weaver

John T Feo

Alessandro Morari

David Nellans

Daniel Joseph Lustig

In general, an application executes on a compute unit, such as a central processing unit (CPU) or graphics processing unit (GPU), to perform some function(s). In some circumstances, improved performance of an application, such as a graphics application, may be provided by executing the application across multiple compute units. However, when using multiple compute units in this manner, synchronization must be provided between the compute units. Synchronization, including the sharing of the data, is typically accomplished through memory. While a shared memory may cause bottlenecks, employing local memory for each compute unit may itself require synchronization (coherence) which can be costly in terms of resources, delay, etc. The present disclosure provides read-write page replication for multiple compute units that avoids the traditional challenges associated with coherence.

Read-write page replication for multiple compute units

A system and method of storing and analyzing information is disclosed. The system includes a compiler layer to convert user queries to data parallel executable code. The system further includes a library of multithreaded algorithms, processes, and data structures. The system also includes a multithreaded runtime library for implementing compiled code at runtime. The executable code is dynamically loaded on computing elements and contains calls to the library of multithreaded algorithms, processes, and data structures and the multithreaded runtime library.

System and method of storing and analyzing information

Growing community of inventors

West Richland, WA, United States of America

Oreste Villa