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  1. Systems & Applications
  2. Parallel algorithms on sequences and strings
  3. Algorithms for Parallel Processing
  4. Parallel and distributed genetic algorithms
  5. Parallel Computing -- from Wolfram MathWorld

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Systems & Applications

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Parallel algorithms on sequences and strings

Constantly aborting computations before they complete would not be a very efficient parallelization strategy. But for many applications, aborted computations are rare enough that they end up squandering less time than the complicated checks and updates required to synchronize tasks in more conventional parallel schemes.

Typically, each atomic task is assigned to a separate processing unit, where it effectively runs in isolation.

Atomic tasks are often fairly substantial. The task of booking an airline flight online, for instance, consists of many separate operations, but they have to be treated as an atomic unit. With speculative execution, large atomic tasks introduce two inefficiencies. The first is that, if the task has to abort, it might do so only after chewing up a lot of computational cycles.


Algorithms for Parallel Processing

Aborting smaller tasks wastes less time. The other is that a large atomic task may have internal subroutines that could be parallelized efficiently. But because the task is isolated on its own processing unit, those subroutines have to be executed serially, squandering opportunities for performance improvements. Ying, and with Joel Emer, a professor of the practice and senior distinguished research scientist at the chip manufacturer NVidia — solves both of these problems.

With Fractal, a programmer adds a line of code to each subroutine within an atomic task that can be executed in parallel. This will typically increase the length of the serial version of a program by a few percent, whereas an implementation that explicitly synchronizes parallel tasks will often increase it by or percent.

Parallel and distributed genetic algorithms

Circuits hardwired into the Fractal chip then handle the parallelization. Swarm was designed to enforce some notion of sequential order in parallel programs. Browse or. Browse Most Popular.

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Parallel Computing -- from Wolfram MathWorld

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