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Detailed simulation experiments demonstrate the effect of various task and processor parameters on the performance of the surveyed algorithms.
These are utilised to obtain an efficient strategy for task to processor allocation achieving an efficiency near its maximum possible value.
Accordingly, several characteristic models describing categories of algorithms are considered and a generalised mathematical model for task to processor allocation in a heterogeneous computing framework is developed and demonstrated.
BfsEnumP1-2 stassignly assign tasks to processors without communication between processors during the construction of a family tree, whereas BfsEnumP3 dynamically makes the assignment depending on computational environment during execution.
Task distribution across processors is managed by the MPI applications programming interface [ 24].
If we assign task 6 to processor 4 rather than to processor 1 in order to better balance the load in term of task completion time, this lead to: P 1 : ?
We develop a fast heuristic for assigning tasks to processors.
Scheduling program tasks on processors is at the core of the efficient use of multiprocessor systems.
Allocating tasks to processors is a well-known NP-Hard problem in distributed computing systems.
Tailored, task-specific processors can sustain the same high-computation throughput and support the same data interfaces as RTL hardware designs.
In this paper we present an automatic approach for statically allocating logical buffers to physical memories, assuming a fixed task-to-processor mapping and respecting multiple throughput constraints.
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