Intel Corporation

Slawomir Putyrski

Francesc Guim Bernat

Susanne M Balle

Evan Custodio

Henry M Mitchel

Joe Grecco

Sujoy Sen

Rahul Khanna

Murugasamy K Nachimuthu

Suraj Prabhakaran

Daniel Rivas Barragan

John Chun Kwok Leung

Paul H Dormitzer

Katalin Klara Bartfai-Walcott

Joseph Butler

Giovani Estrada

Joseph J Grecco

Alexander J Leckey

John Kennedy

Mrittika Ganguli

Thijs Metsch

Chris Woods

Karthik Kumar

Sanjeev N Trika

Qian Li

Arvind Srinivasan

Thomas Willhalm

Andrew J Herdrich

Rameshkumar G Illikkal

Donald Wood

Michael J McGrath

Mark S Myers

Victor Bayon-Molino

Naresh K Sehgal

Connor Upton

Andrzej Kuriata

Teck Joo Goh

Wenhui Shu

Arkadiusz Chylinski

Marek Jakowski

Anna Drewek-Ossowicka

Daniel Richins

Long Cui

Jinshi Chen

Dharmisha Ketankumar Doshi

Mihai Daniel Dodan

Michael Christopher Woods

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.

Technologies for dividing work across accelerator devices

Technologies for offloading acceleration task scheduling operations to accelerator sleds include a compute device to receive a request from a compute sled to accelerate the execution of a job, which includes a set of tasks. The compute device is also to analyze the request to generate metadata indicative of the tasks within the job, a type of acceleration associated with each task, and a data dependency between the tasks.

Technologies for offloading acceleration task scheduling operations to accelerator sleds

Various approaches to efficiently allocating and utilizing hardware resources in data centers while maintaining compliance with a service level objective (SLO) specified for a computational workload is translated into a hardware-level SLO to facilitate direct enforcement by the hardware processor, e.g., using a feedback control loop or model-based mapping of the hardware-level SLO to allocations of microarchitecture resources of the processor. In some embodiments, a computational model of the hardware behavior under resource contention is used to predict the application performance (e.g., as measured in terms of the hardware-level SLO) to be expected under certain contention scenarios. Scheduling of workloads among the compute nodes within the data center may be based on such predictions. In further embodiments, configurations of microservices are optimized to minimize hardware resources while meeting a specified performance goal.

Efficient resource allocation for service level compliance

Technologies for providing accelerated functions as a service in a disaggregated architecture include a compute device that is to receive a request for an accelerated task. The task is associated with a kernel usable by an accelerator sled communicatively coupled to the compute device to execute the task. The compute device is further to determine, in response to the request and with a database indicative of kernels and associated accelerator sleds, an accelerator sled that includes an accelerator device configured with the kernel associated with the request. Additionally, the compute device is to assign the task to the determined accelerator sled for execution. Other embodiments are also described and claimed.

Technologies for providing accelerated functions as a service in a disaggregated architecture

Technologies for providing efficient reprovisioning in an accelerator device include an accelerator sled. The accelerator sled includes a memory and an accelerator device coupled to the memory. The accelerator device is to configure itself with a first bit stream to establish a first kernel, execute the first kernel to produce output data, write the output data to the memory, configure itself with a second bit stream to establish a second kernel, and execute the second kernel with the output data in the memory used as input data to the second kernel. Other embodiments are also described and claimed.

Technologies for providing efficient reprovisioning in an accelerator device

Examples described herein relate to prefetching content from a remote memory device to a memory tier local to a higher level cache or memory. An application or device can indicate a time availability for data to be available in a higher level cache or memory. A prefetcher used by a network interface can allocate resources in any intermediary network device in a data path from the remote memory device to the memory tier local to the higher level cache. Memory access bandwidth, egress bandwidth, memory space in any intermediary network device can be allocated for prefetch of content. In some examples, proactive prefetch can occur for content expected to be prefetched but not requested to be prefetched.

Proactive data prefetch with applied quality of service

Technologies for providing I/O channel abstraction for accelerator device kernels include an accelerator device comprising circuitry to obtain availability data indicative of an availability of one or more accelerator device kernels in a system, including one or more physical communication paths to each accelerator device kernel. The circuitry is also configured to determine whether to establish a logical communication path between a kernel of the present accelerator device and another accelerator device kernel and establish, in response to a determination to establish the logical communication path as a function of the obtained availability data, the logical communication path between the kernel of the present accelerator device and the other accelerator device kernel.

Technologies for establishing communication channel between accelerator device kernels

Technologies for latency based service level agreement (SLA) management in remote direct memory access (RDMA) networks include multiple compute devices in communication via a network switch. A compute device determines a service level objective (SLO) indicative of a guaranteed maximum latency for a percentage of RDMA requests of an RDMA session. The compute device receives latency data indicative of latency of an RDMA request from a host device. The compute device determines a priority associated with the RDMA request as a function of the SLO and the latency data. The compute device schedules the RDMA request based on the priority. The network switch may allocate queue resources to the RDMA request based on the priority, reclaim the queue resources after the RDMA request is scheduled, and then return the queue resources to a free pool. Other embodiments are described and claimed.

Technologies for latency based service level agreement management in remote direct memory access networks

Techniques for managing static and dynamic partitions in software-defined infrastructures (SDI) are described. An SDI manager component may include one or more processor circuits to access one or more resources. The SDI manager component may include a partition manager to create one or more partitions using the one or more resources, the one or more partitions each including a plurality of nodes of a similar resource type. The SDI manager may generate an update to a pre-composed partition table, stored within a non-transitory computer-readable storage medium, including the created one or more partitions, and receive a request from an orchestrator for a node. The SDI manager may select one of the created one or more partitions to the orchestrator based upon the pre-composed partition table, and identify the selected partition to the orchestrator. Other embodiments are described and claimed.

Methods and apparatus for composite node creation and management through SDI partitions

Techniques for migration for composite nodes in software-defined infrastructures (SDI) are described. A SDI system may include a SDI manager component, including one or more processor circuits, configured to access one or more remote resources, the SDI manager component may include a partition manager configured to receive a request to create a composite node from an orchestrator component, the request including at least one preferred compute sled type and at least one alternative compute sled type. The SDI manager may create a composite node using a first compute sled matching the at least one alternative compute sled type. The SDI manager may determine, based upon a migration table stored on a non-transitory computer-readable storage medium that a second compute sled matching the at least one preferred compute sled type is available. The SDI manager may perform an migration from the first compute sled to the second compute sled. Other embodiments are described and claimed.

Methods and apparatus for SDI support for automatic and transparent migration

Technologies for providing advanced resource management in a disaggregated environment include a compute device. The compute device includes circuitry to obtain a workload to be executed by a set of resources in a disaggregated system, query a sled in the disaggregated system to identify an estimated time to complete execution of a portion of the workload to be accelerated using a kernel, and assign, in response to a determination that the estimated time to complete execution of the portion of the workload satisfies a target quality of service associated with the workload, the portion of the workload to the sled for acceleration.

Technologies for providing advanced resource management in a disaggregated environment

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Gdynia, Poland

Slawomir Putyrski