BARRIERS AND SYNCHRONIZATION FOR MACHINE LEARNING AT AUTONOMOUS MACHINES

• Main Authors: KOKER ALTUG, HURD LINDA L, RANGANATHAN VASANTH, VEMBU BALAJI, WEAST JOHN C, MACPHERSON MIKE B, KIM DUKHWAN, RAY JOYDEEP, JAHAGIRDAR SANJEEV, APPU ABHISHEK R
• Format: Patent
• Language: Chinese; English
• Published: 23.11.2018
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

The application discloses barriers and synchronization for machine learning at autonomous machines. A mechanism is described for facilitating barriers and synchronization for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting thread groups relating to machine learning associated with one or more processing devices. The method may further include facilitating barrier synchronization of the thread groups across multiple dies such that each thread in a thread group is scheduled across a set of compute elements associated with the multiple dies, where each die represents a processing device of the one or more processing devices, the processing device including a graphics processor. 本申请公开了对自主机器处的机器学习进行屏障和同步。描述了种用于促进对自主机器处的机器学习进行屏障和同步的机制。如本文所描述的实施例的种方法包括：检测与关联于个或多个处理装置的机器学习相关的线程组。所述方法可以进步包括：促进所述线程组跨多个管芯的屏障同步，使得线程组中的每个线程跨与所述多个管芯相关联的组计算元件而被调度，其中，每个管芯表示所述个或多个处理装置中的处理装置，所述处理装置包括图形处理器。