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A Proposal for Parallel Self-Adjusting Computation Matthew Hammer Umut A. Acar
 

Summary: A Proposal for Parallel Self-Adjusting Computation
Matthew Hammer Umut A. Acar
Toyota Technological Institute,
Chicago, IL
{hammer,umut}@tti-c.org.
Mohan Rajagopalan Anwar Ghuloum
Programming Systems Lab, Intel,
Santa Clara, CA.
{mohan.rajagopalan,anwar.ghuloum}@intel.com.
ABSTRACT
We present an overview of our ongoing work on paralleliz-
ing self-adjusting-computation techniques. In self-adjusting
computation, programs can respond to changes to their data
(e.g., inputs, outcomes of comparisons) automatically by
running a change-propagation algorithm. This ability is
important in applications where inputs change slowly over
time. All previously proposed self-adjusting computation
techniques assume a sequential execution model. We de-
scribe techniques for writing parallel self-adjusting programs
and a change propagation algorithm that can update compu-

  

Source: Acar, Umut - Programming Languages and Systems Group, Max-Planck Institute for Software Systems

 

Collections: Computer Technologies and Information Sciences