Techniques are provided for comparing multi-level data structures using commutative digesting for unordered data collections. One method comprises obtaining two multi-level data structures, wherein at least one multi-level data structure comprises an unordered data collection; determining a data structure digest value for each the two multi-level data structures by accumulating a data element digest value for each data element of the respective multi-level data structure, wherein a data element digest value for a given data element comprising an unordered data collection is determined using a commutative accumulator function; and evaluating a similarity of the two multi-level data structures by comparing the respective data structure digest values. A data element digest value for a given data element comprising an ordered data collection can be determined using a noncommutative accumulator function that aggregates a digest value for each data element using a noncommutative operation.

A bag transfer mechanism for moving intravenous medication delivery bags includes linear actuator and a pantograph mechanism. A proximal end of the pantograph mechanism is coupled to the linear actuator such a that the pantograph mechanism is configured to extend when the linear actuator travels in a first direction, and to retract when the linear actuator travels in a second direction. The bag transfer mechanism also includes a magnet coupled to a distal end of the pantograph mechanism.

A method for displaying messages receiving from a social network system, a plurality of messages, and filtering the plurality of messages into at least two filtered sets of messages based on at least one feature of the plurality of messages where each of the at least two filtered sets of messages includes a different subset of the plurality of messages. The method can include assigning a first of two filtered sets of messages to a first column, analyzing an interaction of the user with the first of the two filtered set of messages, and triggering display of a second of the two filtered sets of messages in a second column in response to the interaction.

A method for displaying messages receiving from a social network system, a plurality of messages, and filtering the plurality of messages into at least two filtered sets of messages based on at least one feature of the plurality of messages where each of the at least two filtered sets of messages includes a different subset of the plurality of messages. The method can include assigning a first of two filtered sets of messages to a first column, analyzing an interaction of the user with the first of the two filtered set of messages, and triggering display of a second of the two filtered sets of messages in a second column in response to the interaction.

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. Additionally the compute device is to send an availability request, including the metadata, to one or more micro-orchestrators of one or more accelerator sleds communicatively coupled to the compute device. The compute device is further to receive availability data from the one or more micro-orchestrators, indicative of which of the tasks the micro-orchestrator has accepted for acceleration on the associated accelerator sled. Additionally, the compute device is to assign the tasks to the one or more micro-orchestrators as a function of the availability data.

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. Additionally the compute device is to send an availability request, including the metadata, to one or more micro-orchestrators of one or more accelerator sleds communicatively coupled to the compute device. The compute device is further to receive availability data from the one or more micro-orchestrators, indicative of which of the tasks the micro-orchestrator has accepted for acceleration on the associated accelerator sled. Additionally, the compute device is to assign the tasks to the one or more micro-orchestrators as a function of the availability data.

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 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 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 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.