Abstract: Disclosed herein are technologies directed to discovering semantic similarities between images and text, which can include performing image search using a textual query, performing text search using an image as a query, and/or generating captions for images using a caption generator. A semantic similarity framework can include a caption generator and can be based on a deep multimodal similar model. The deep multimodal similarity model can receive sentences and determine the relevancy of the sentences based on similarity of text vectors generated for one or more sentences to an image vector generated for an image. The text vectors and the image vector can be mapped in a semantic space, and their relevance can be determined based at least in part on the mapping. The sentence associated with the text vector determined to be the most relevant can be output as a caption for the image.

Abstract: 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.

Abstract: Disclosed herein are technologies directed to discovering semantic similarities between images and text, which can include performing image search using a textual query, performing text search using an image as a query, and/or generating captions for images using a caption generator. A semantic similarity framework can include a caption generator and can be based on a deep multimodal similar model. The deep multimodal similarity model can receive sentences and determine the relevancy of the sentences based on similarity of text vectors generated for one or more sentences to an image vector generated for an image. The text vectors and the image vector can be mapped in a semantic space, and their relevance can be determined based at least in part on the mapping. The sentence associated with the text vector determined to be the most relevant can be output as a caption for the image.

Abstract: 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.