Nvidia Corporation

Vivek Kini

Mark Hairgrove

Stephen Jones

Cameron Buschardt

Lucien Dunning

David Fontaine

John Hubbard

Piotr Jaroszynski

Christopher Frederick Lamb

Paul J Sidenblad

Jaydeep Marathe

Vyas Venkataraman

Bastiaan Aarts

Kyrylo Perelygin

Timothy James Murray

Gaurav Dadwal

Cory Perry

Forrest Iandola

Michael Christopher Delorme

Ajit Panditrao Hakke Patil

Prasad Marathe

Apparatuses, systems, and techniques to facilitate memory management. In at least one embodiment, data from one or more first shared physical memory locations is accessed based, at least in part, on one or more virtual addresses corresponding to one or more second shared physical memory locations.

Sharing memory among multiple processors

Apparatuses, systems, and techniques to manage memory arrays. In at least one embodiment an application programming interface (API) is performed to disassociate a virtual address indicated by the API from a corresponding physical address.

Application programming interface to disassociate a virtual address

The present invention facilitates efficient and effective utilization of unified virtual addresses across multiple components. In one exemplary implementation, an address allocation process comprises: establishing space for managed pointers across a plurality of memories, including allocating one of the managed pointers with a first portion of memory associated with a first one of a plurality of processors; and performing a process of automatically managing accesses to the managed pointers across the plurality of processors and corresponding memories. The automated management can include ensuring consistent information associated with the managed pointers is copied from the first portion of memory to a second portion of memory associated with a second one of the plurality of processors based upon initiation of an accesses to the managed pointers from the second one of the plurality of processors.

Unified memory systems and methods

A software development environment (SDE) and a method of compiling integrated source code. One embodiment of the SDE includes: (1) a parser configured to partition an integrated source code into a host code partition and a device code partition, the host code partition including a reference to a device variable, (2) a translator configured to: (2a) embed device machine code, compiled based on the device code partition, into a modified host code, (2b) define a pointer in the modified host code configured to be initialized, upon execution of the integrated source code, to a memory address allocated to the device variable, and (2c) replace the reference with a dereference to the pointer, and (3) a host compiler configured to employ a host library to compile the modified host code.

Software development environment and method of compiling integrated source code

A method for handling parallel processing clients associated with a server in a GPU, the method comprising: receiving a failure indication for at least client running a thread in the GPU; determining threads in the GPU associated with the failing client; exiting threads in the GPU associated with the failing client; and continuing to execute remaining threads in the GPU for other clients running threads in the GPU.

Selectively killing trapped multi-process service clients sharing the same hardware context

One embodiment sets forth a method for assigning priorities to kernels launched by a software application and executed within a stream of work on a parallel processing subsystem. First, the software application assigns a desired priority to a stream using a call included in the API. The API receives this call and passes it to a driver. The driver maps the desired priority to an appropriate device priority associated with the parallel processing subsystem. Subsequently, if the software application launches a particular kernel within the stream, then the driver assigns the device priority associated with the stream to the kernel before adding the kernel to the stream for execution on the parallel processing subsystem. Advantageously, by assigning priorities to streams and, subsequently, strategically launching kernels within the prioritized streams, an application developer may fine-tune the software application to increase the overall processing efficiency of the software application.

Assigning priorities to computational work streams by mapping desired execution priorities to device priorities

One embodiment sets forth a method for assigning priorities to kernels launched by a software application and executed within a stream of work on a parallel processing subsystem that supports dynamic parallelism. First, the software application assigns a maximum nesting depth for dynamic parallelism. The software application then assigns a stream priority to a stream. These assignments cause a driver to map the stream priority to a device priority and, subsequently, associate the device priority with the stream. As part of the mapping, the driver ensures that each device priority is at least the maximum nesting depth higher than the device priorities associated with any lower priority streams. Subsequently, the driver launches any kernel included in the stream with the device priority associated with the stream. Advantageously, by strategically assigning the maximum nesting depth and prioritizing streams, an application developer may increase the overall processing efficiency of the software application.

Techniques for sharing priorities between streams of work and dynamic parallelism

One embodiment sets forth a method for guiding the order in which a parallel processing subsystem executes memory copies. A driver creates semaphores for all but the lowest priority included in a plurality of priorities and associates one priority with each copy hardware channel included in the parallel processing subsystem. The driver then aliases prioritized streams to the copy hardware channels based on the priorities. Upon receiving a request to execute a memory copy within one of the streams, the driver inserts commands into the aliased copy hardware channel. These commands use the semaphores to direct the parallel processing subsystem to execute the memory copy based on the priority of the copy hardware channel. Advantageously, by assigning priorities to streams and, subsequently, strategically requesting memory copies within the prioritized streams, an application developer may fine-tune their software application to increase the overall processing efficiency of the software application.

Growing community of inventors

Sunnyvale, CA, United States of America

Vivek Kini