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Self-Adjusting Computation (An Overview)

Summary: Self-Adjusting Computation
(An Overview)
Umut A. Acar
Toyota Technological Institute at Chicago
Many applications need to respond to incremental modifications
to data. Being incremental, such modification often require incre-
mental modifications to the output, making it possible to respond
to them asymptotically faster than recomputing from scratch. In
many cases, taking advantage of incrementality therefore dramati-
cally improves performance, especially as the input size increases.
As a frame of reference, note that in parallel computing speedups
are bounded by the number of processors, often a (small) constant.
Designing and developing applications that respond to incre-
mental modifications, however, is challenging: it often involves
developing highly specific, complex algorithms. Self-adjusting
computation offers a linguistic approach to this problem. In self-
adjusting computation, programs respond automatically and ef-
ficiently to modifications to their data by tracking the dynamic


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


Collections: Computer Technologies and Information Sciences