Abstract: Examples relate to an apparatus, a device, a method, and a computer program for scheduling an execution of compute kernels on one or more computing devices, and to a computer system comprising such an apparatus or device. The apparatus comprises processing circuitry and interface circuitry. The processing circuitry is configured to determine an impending execution of two or more compute kernels to the one or more computing devices. The processing circuitry is configured to pipeline a data transfer related to the execution of the two or more compute kernels to the one or more computing devices via the interface circuitry.

Abstract: An apparatus to facilitate data parallel programming-based transparent transfer across heterogeneous devices is disclosed. The apparatus includes a processor to: identify a change in device status that triggers a device transfer process from an original device, wherein the original device is associated with a queue of an application program of a data parallel programming runtime; identify a new device that is compatible with the original device; migrate at least one of a state or data of the original device to the new device; logically map, without user intervention, the queue to the new device in the data parallel programming runtime; and initiate execution of the application program on the new device using the queue.

Abstract: An apparatus to facilitate data parallel programming task graph optimization through device telemetry is disclosed. The apparatus includes a processor to: receive, from a compiler, compiled code generated from source code of an application, the compiled code to support a workload of the application; generate a task graph of the application using the compiled code, the task graph to represent at least one of a relationship or dependency of the compiled code; receive runtime telemetry data corresponding to execution of the compiled code on the one or more accelerator devices; identify one or more scheduling optimizations for the one or more accelerator devices based on the task graph and the received telemetry data; and provide a scheduling command to cause the one or more scheduling optimizations to be implemented in the one or more accelerator devices.

Abstract: In one example, a system for generating vector based selection control statements can include a processor to determine a vector cost of the selection control statement is below a scalar cost and determine the selection control statement is to be executed in a sorted order based on dependencies between branch instructions of the selection control statement. The processor can also determine a program ordering of labels of the selection control statement does not match a mathematical ordering of the labels and execute the selection control statement with a vector of values, wherein the selection control statement is to be executed based on a jump table and a sorted unique value technique, wherein the sorted unique value technique comprises selecting at least one of the plurality of branch instructions from the jump table.

Abstract: In one example, a system for generating vector based selection control statements can include a processor to determine a vector cost of the selection control statement is below a scalar cost and determine the selection control statement is to be executed in a sorted order based on dependencies between branch instructions of the selection control statement. The processor can also determine a program ordering of labels of the selection control statement does not match a mathematical ordering of the labels and execute the selection control statement with a vector of values, wherein the selection control statement is to be executed based on a jump table and a sorted unique value technique, wherein the sorted unique value technique comprises selecting at least one of the plurality of branch instructions from the jump table.