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Task partitioning upon memory-constrained multiprocessors Nathan Fisher James H. Anderson Sanjoy Baruah
 

Summary: Task partitioning upon memory-constrained multiprocessors
Nathan Fisher James H. Anderson Sanjoy Baruah
Department of Computer Science
The University of North Carolina at Chapel Hill
{fishern, anderson, baruah}@cs.unc.edu
Abstract
Most prior theoretical research on partitioning algo-
rithms for real-time multiprocessor platforms has focused
on ensuring that the cumulative computing requirements of
the tasks assigned to each processor does not exceed the
processor's processing power. However, many multipro-
cessor platforms have only limited amounts of local per-
processor memory; if the memory limitation of a processor
is not respected, thrashing between "main" memory and the
processor's local memory may occur during run-time and
may result in performance degradation. We formalize the
problem of task partitioning in a manner that is cognizant
of both memory and processing capacity constraints as the
memory constrained multiprocessor partitioning problem,
prove that this problem is intractable, and present efficient

  

Source: Anderson, James - Department of Computer Science, University of North Carolina at Chapel Hill

 

Collections: Computer Technologies and Information Sciences