Intel Corporation

Renji Thomas

Jianfang Olena Zhu

Deepak Samuel Kirubakaran

Guy M Therien

James G Hermerding, Ii

Russell Jerome Fenger

Chee Lim Nge

Premanand Sakarda

Rajshree Chabukswar

Bo Qiu

Srikanth Potluri

Mark J Gallina

Monica Gupta

Jianwei Dai

Ashraf H Wadaa

Akhilesh P Rallabandi

Columbia Mishra

Michael Kishinevsky

Carin Ruiz

Chris Binns

Ahmed Shams

Ramakrishnan Sivakumar

Pietro Mercati

Chad Gutierrez

Arijit Chattopadhyay

James Hermerding Ii

A hardware and software coordinated processor power state policy (e.g., policy for C-state) that delivers optimal power state selection by taking in to account the performance and/or responsiveness needs of thread expected to be scheduled on the core entering idle, to achieve improved IPC and performance for cores running user critical tasks. The scheme provides the ability to deliver responsiveness gains for important and/or user-critical threads running on a system-on-chip. A power management controller coupled to the plurality of processing cores, wherein the power management controller receives a hint from an operating system indicative of a bias towards a power state or performance state for at least one of the processing cores of the plurality of processing cores based on a priority of a thread in context switch.

Hardware and software coordinated cost-aware low power state selection

Methods, apparatus, and systems to dynamically schedule a workload to among compute blocks based on temperature are disclosed. An apparatus to schedule a workload to at least one of a plurality of compute blocks based on temperature includes a prediction engine to determine (i) a first predicted temperature of a first compute block of the plurality of compute blocks and (ii) a second predicted temperature of a second compute block of the plurality of compute blocks. The apparatus also includes a selector to select between the first compute block and the second compute block for assignment of the workload. The selection is based on which of the first and second predicted temperatures is lower. The apparatus further includes a workload scheduler to assign the workload to the selected one of the first or second compute blocks.

Methods, apparatus, and systems to dynamically schedule workloads among compute resources based on temperature

An apparatus comprising: a model to generate adjusted tuning parameters of a thread scheduling policy based on a tradeoff indication value of a target system; and a workload monitor to: execute a workload based on the thread scheduling policy; obtain a performance score and a power score from the target system based on execution of the workload, the performance score and the power score corresponding to a tradeoff indication value; compare the tradeoff indication value to a criterion; and based on the comparison, initiate the model to re-adjust the adjusted tuning parameters.

Methods, systems, articles of manufacture, and apparatus to optimize thread scheduling

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Hillsboro, OR, United States of America

Renji Thomas