Intel Corporation

Neta Zmora

Eran Ben-Avi

Tomer Bar-On

Jeremie Dreyfuss

Yaniv Fais

Lev Faivishevsky

Jacob Subag

Amit Bleiweiss

Tomer Schwartz

Guy Jacob

Zigi Walter

Orly Weisel

Shira Hirsch

Yarden Oren

In an example, an apparatus comprises a plurality of compute engines; and logic, at least partially including hardware logic, to detect a cache line conflict in a last-level cache (LLC) communicatively coupled to the plurality of compute engines; and implement context-based eviction policy to determine a cache way in the cache to evict in order to resolve the cache line conflict. Other embodiments are also disclosed and claimed.

System cache optimizations for deep learning compute engines

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 an example, an apparatus comprises logic, at least partially including hardware logic, to save one or more outputs of a deep learning neural network in a storage system of an autonomous vehicle and upload the one or more outputs to a remote server. Other embodiments are also disclosed and claimed.

Storage system of DNN outputs for black box

Growing community of inventors

Tzur Moshe, Israel

Neta Zmora