Abstract: A method of performing automatic tuning on a deep learning model includes: utilizing an instruction-based learned cost model to estimate a first type of operational performance metrics based on a tuned configuration of layer fusion and tensor tiling; utilizing statistical data gathered during a compilation process of the deep learning model to determine a second type of operational performance metrics based on the tuned configuration of layer fusion and tensor tiling; performing an auto-tuning process to obtain a plurality of optimal configurations based on the first type of operational performance metrics and the second type of operational performance metrics; and configure the deep learning model according to one of the plurality of optimal configurations.

Abstract: A device includes: a complementary transistor including: a first transistor having a first source/drain region and a second source/drain region; and a second transistor stacked on the first transistor, and having a third source/drain region and a fourth source/drain region, the third source/drain region overlapping the first source/drain region, the fourth source/drain region overlapping the second source/drain region. The device further includes: a first source/drain contact electrically coupled to the third source/drain region; a second source/drain contact electrically coupled to the second source/drain region; a gate isolation structure adjacent the first and second transistors; and an interconnect structure electrically coupled to the first source/drain contact and the second source/drain contact.

Abstract: A modular control system for controlling an AGV includes an interface, a processor, a memory, and a plurality of programs. The plurality of programs include a task scheduling module, a sensor fusion module, a mapping module, and a localization module. The interface receives a command signal from an AGV management system and sensor signals from a plurality of sensors. The memory stores a surrounding map and the plurality of programs to be executed by the processor. The task scheduling module converts the command signal to generate an enabling signal. The sensor fusion module processes the received sensor signals according to the enabling signal and generates an organized sensor data. The mapping module processes the organized sensor data and the surrounding map to generate an updated surrounding map. The localization module processes the organized sensor data and the updated surrounding map to generate a location and pose signal.

Abstract: An optical fiber adapter includes an adapter body defining multiple first accommodation chambers and second accommodation chambers in opposing first mating portion and second mating portion thereof, a partition wall disposed between the first accommodation chambers and the second accommodation chambers, coupling portions respectively extended from the partition wall into the first accommodation chamber and the second accommodation chamber and two wings respectively vertically extended from opposing top and bottom sides of the partition wall, and ferrules respectively mounted in the coupling portions for guiding the optical fiber cores of each two respective optical fiber connectors into abutment for transmitting an optical signal. Subject to the design of the wings, a large number of optical fiber adapters can be closely mounted in a device housing having a limited width and height.

Abstract: To minimize the space requirement inside a cassette and make cable retention force consistent and easy for fiber routing/rework, a cassette includes a cassette base molded to include a plurality of holders, a cassette cover to close the cassette base, and a plurality of blocks, respectively disposed into the holders, each of the blocks including one or more holes to accommodate one or more fiber cables. The fiber cables are fixed in the holes using a type of adhesive. In addition, bare fibers are placed inside the cassette to communicate respectively with the fiber cables.