Abstract: 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.

Abstract: Technologies for migrating data between edge accelerators hosted on different edge locations include a device hosted on a present edge location. The device includes one or more processors to: receive a workload from a requesting device, determine one or more accelerator devices hosted on the present edge location to perform the workload, and transmit the workload to the one or more accelerator devices to process the workload. The one or more processor is further to determine whether to perform data migration from the one or more accelerator devices to one or more different edge accelerator devices hosted on a different edge location, and send, in response to a determination to perform the data migration, a request to the one or more accelerator devices on the present edge location for transformed workload data to be processed by the one or more different edge accelerator devices.

Abstract: Technologies for securely providing one or more remote accelerators hosted on edge resources to a client compute device includes a device that further includes an accelerator and one or more processors. The one or more processors are to determine whether to enable acceleration of an encrypted workload, receive, via an edge network, encrypted data from a client compute device, and transfer the encrypted data to the accelerator without exposing content of the encrypted data to the one or more processors. The accelerator is to receive, in response to a determination to enable the acceleration of the encrypted workload, an accelerator key from a secure server via a secured channel, and process, in response to a transfer of the encrypted data from the one or more processors, the encrypted data using the accelerator key.

Abstract: 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.

Abstract: 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.

Abstract: A device includes a programmable logic fabric. The programmable logic fabric includes a first area, wherein a first persona is configured to be programmed in the first area. The programmable logic fabric also includes a second area, wherein a second persona is configured to be programmed in the second area in a second persona programming time. The device is configured to be controlled by a host to switch from running the first persona to running the second persona in a time less than the second persona programming time.

Abstract: A compute device to manage workflow to disaggregated computing resources is provided. The compute device comprises a compute engine receive a workload processing request, the workload processing request defined by at least one request parameter, determine at least one accelerator device capable of processing a workload in accordance with the at least one request parameter, transmit a workload to the at least one accelerator device, receive a work product produced by the at least one accelerator device from the workload, and provide the work product to an application.

Abstract: Technologies for providing shared memory for accelerator sleds includes an accelerator sled to receive, with a memory controller, a memory access request from an accelerator device to access a region of memory. The request is to identify the region of memory with a logical address. Additionally, the accelerator sled is to determine from a map of logical addresses and associated physical address, the physical address associated with the region of memory. In addition, the accelerator sled is to route the memory access request to a memory device associated with the determined physical address.

Abstract: Technologies for securely providing one or more remote accelerators hosted on edge resources to a client compute device includes a device that further includes an accelerator and one or more processors. The one or more processors are to determine whether to enable acceleration of an encrypted workload, receive, via an edge network, encrypted data from a client compute device, and transfer the encrypted data to the accelerator without exposing content of the encrypted data to the one or more processors. The accelerator is to receive, in response to a determination to enable the acceleration of the encrypted workload, an accelerator key from a secure server via a secured channel, and process, in response to a transfer of the encrypted data from the one or more processors, the encrypted data using the accelerator key.

Abstract: 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.

Abstract: Technologies for compressing communications for accelerator devices are disclosed. An accelerator device may include a communication abstraction logic units to manage communication with one or more remote accelerator devices. The communication abstraction logic unit may receive communication to and from a kernel on the accelerator device. The communication abstraction logic unit may compress and decompress the communication without instruction from the corresponding kernel. The communication abstraction logic unit may choose when and how to compress communications based on telemetry of the accelerator device and the remote accelerator device.

Abstract: A device includes a programmable logic fabric. The programmable logic fabric includes a first area, wherein a first persona is configured to be programmed in the first area. The programmable logic fabric also includes a second area, wherein a second persona is configured to be programmed in the second area in a second persona programming time. The device is configured to be controlled by a host to switch from running the first persona to running the second persona in a time less than the second persona programming time.

Abstract: 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.

Abstract: Technologies for migrating data between edge accelerators hosted on different edge locations include a device hosted on a present edge location. The device includes one or more processors to: receive a workload from a requesting device, determine one or more accelerator devices hosted on the present edge location to perform the workload, and transmit the workload to the one or more accelerator devices to process the workload. The one or more processor is further to determine whether to perform data migration from the one or more accelerator devices to one or more different edge accelerator devices hosted on a different edge location, and send, in response to a determination to perform the data migration, a request to the one or more accelerator devices on the present edge location for transformed workload data to be processed by the one or more different edge accelerator devices.

Abstract: 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.

Abstract: Technologies for determining a set of edge resources to offload a workload from a client compute device based on a brokering logic provided by a service provider include a device that includes circuitry that is in communication with edge resources. The circuitry is to receive a brokering logic from a service provider receive a request from a client compute device, wherein the request includes a function to be used to execute the request and one or more parameters associated with the client compute device, determine the one or more parameters, select, as a function of the one or more parameters and the brokering logic, a physical implementation to perform the function, wherein the physical implementation indicates a set of edge resources and a performance level for each edge resource of the set of edge resources, and perform, in response to a selection of the physical implementation, the request using the set of edge resources associated with the physical implementation.

Abstract: Technologies for securely providing one or more remote accelerators hosted on edge resources to a client compute device includes a device that further includes an accelerator and one or more processors. The one or more processors are to determine whether to enable acceleration of an encrypted workload, receive, via an edge network, encrypted data from a client compute device, and transfer the encrypted data to the accelerator without exposing content of the encrypted data to the one or more processors. The accelerator is to receive, in response to a determination to enable the acceleration of the encrypted workload, an accelerator key from a secure server via a secured channel, and process, in response to a transfer of the encrypted data from the one or more processors, the encrypted data using the accelerator key.

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

Abstract: Technologies for fulfilling service requests in an edge architecture include an edge gateway device to receive a request from an edge device or an intermediate tier device of an edge network to perform a function of a service by an entity hosting the service. The edge gateway device is to identify one or more input data to fulfill the request by the service and request the one or more input data from an edge resource identified to provide the input data. The edge gateway device is to provide the input data to the entity associated with the request.

Abstract: 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.