Intel Corporation

Orly Weisel

Tomer Bar-On

Jeremie Dreyfuss

Yaniv Fais

Lev Faivishevsky

Jacob Subag

Eran Ben-Avi

Guy Jacob

Zigi Walter

Neta Zmora

Shira Hirsch

Yarden Oren

Avigdor Dori Eldar

Maoz Madmony

Ofir Levy

Alexandra Manevitch

Raizy Kellerman

Amos Goldman

Noam Teomim

Liad Aben Zour

In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to traverse a solution space, score a plurality of solutions to a scheduling deep learning network execution, and select a preferred solution from the plurality of solutions to implement the deep learning network. Other embodiments are also disclosed and claimed.

Scheduling configuration for deep learning networks

In accordance with some embodiments, connected-component labeling is performed in both the screen dimensions (which may be referred to as the x and y dimensions) and a depth dimension to label objects in a depth image. Then the contour of labeled blobs may be used to identify an object in the depth image. Using contours may be advantageous in some embodiments because it reduces the amount of data that must be handled and the extent of computations, compared to conventional techniques which use bit map based operations.

Locating objects within depth images

Systems and methods may provide for obtaining data associated with an image and using a plurality of threads in a graphics processor to conduct a single instruction multiple data (SIMD) scan of the data. Additionally, systems and methods may provide for generating a plurality of connection tables corresponding to the plurality of threads based on the SIMD scan. In one example, a plurality of threads in the graphics processor are used to conduct a single phase merge of the plurality of connection tables onto a global connected components labeling (CCL) table for the image.

Connected component labeling in graphics processors

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Elazar, Israel

Orly Weisel