Intel Corporation

Vishal Verma

Mohan J Kumar

Rahul Khanna

Ashok Raj

Ziye Yang

Narayan Ranganathan

Gang Cao

Sivakumar Radhakrishnan

Changpeng Liu

James R Harris

Benjamin Walker

Chet R Douglas

Kushal Datta

Vikram A Saletore

Chong Han

Dan J Williams

Meenakshi Arunachalam

Deepthi Karkada

Vamsi Sripathi

Examples herein relate to polling for input/output transactions of a network interface or a storage device, or any peripheral device. Some examples monitor clock cycles spent checking for a presence of input/output (I/O) events and processing I/O events and monitor clock cycles spent checking for presence of I/O events without completing an I/O event. Central processing unit (CPU) core utilization can be based on clock cycles spent checking for a presence of I/O events and processing I/O events and clock cycles spent checking for presence of I/O events without completion of an I/O event. For example, if core utilization is below a threshold, frequency of the core can be reduced for performing polling of I/O events. If core utilization is at or above the threshold, frequency of the core can be increased used to performing polling of I/O events.

Adaptive processor resource utilization

Systems, apparatuses and methods may provide for technology that identifies a first set of compute nodes and a second set of compute nodes, wherein the first set of compute nodes execute more slowly than the second set of compute nodes. The technology may also automatically determine a compute node configuration that results in a relatively low difference in completion time between the first set of compute nodes and the second set of compute nodes with respect to a neural network workload. In an example, the technology applies the compute node configuration to an execution of the neural network workload on one or more nodes in the first set of compute nodes and one or more nodes in the second set of compute nodes.

Automated resource usage configurations for deep learning neural network workloads on multi-generational computing architectures

In one embodiment, a block data transfer interface employing offload data transfer engine in accordance with the present description includes an offload data transfer engine executing a data transfer command set to transfer a block of data in a transfer data path from a source memory to a new region of a destination memory, wherein the transfer data path bypasses a central processing unit to minimize or reduce involvement of the central processing unit in the block transfer. In response to a successful transfer indication, a logical address is re-mapped to a physical address of the new region of the destination memory, instead of a physical address of the original region of the destination memory. In one embodiment, the re-mapping is performed by a central processing unit. In another embodiment, the re-mapping is performed by the offload data transfer engine. Other aspects are described herein.

Offload data transfer engine for a block data transfer interface

Growing community of inventors

Chandler, AZ, United States of America

Vishal Verma