to parallelize

27 examples (0.02 sec)
  • Often this task is difficult since the programmer who wants to parallelize the code has not originally written the code under consideration.
  • Those loops are not only hard to parallelize, but they also perform horribly.
  • Scale-out, in-memory technology allows smart caching for small or huge datasets using more computers to parallelize the efforts, as needed.
  • Sequential languages are notoriously difficult to parallelize in general, so efficient parallel implementations will usually require significant guidance from the user.
  • Additionally, it is difficult to parallelize the partitioning step efficiently in-place.
  • Similarly there are problems in P that are not known to be either P-complete or NC, but are thought to be difficult to parallelize.
  • Though it had not been the original intent, these new approaches allowed the language to parallelize a large percentage of the operations it performed, transparently to the programmer.
  • Virtual synchrony permits a multi-primary approach in which a group of processes cooperate to parallelize some aspects of request processing.
  • With the image sensor and image processing combined on the same die it is essentially possible to parallelize image processing up to the level where each pixel has its dedicated image processing logic.
  • This need to parallelize applications is partially addressed by tools that analyze code to exploit parallelism.
  • It is clear that this problem is P-complete: if we can parallelize a general simulation of a sequential computer, then we will be able to parallelize any program that runs on that computer.
  • A subset of traditional applications are often difficult to parallelize and make use of additional CPU hardware available on the platform, restraining applications to use only one CPU.
  • CABAC is also difficult to parallelize and vectorize, so other forms of parallelism (such as spatial region parallelism) may be coupled with its use.
  • According to this test, by comparing the indices of two arrays present in two or more statements, it can be calculated whether it is legal to parallelize the loop or not.
  • Embarrassingly parallel applications are considered the easiest to parallelize.
  • Because the non-bonded forces are short-ranged in DPD, it is possible to parallelize a DPD code very efficiently using a spatial domain decomposition technique.
  • Thus SCU requires explicit partitioning (manual partitioning or "sharding" into multiple units) to parallelize compilation.
  • Also, serial tasks like decoding the entropy encoding algorithms used in video codecs are impossible to parallelize because each result generated is used to help create the next result of the entropy decoding algorithm.
  • Although pointer jumping specifically finds the roots of a forest of rooted trees, pointer jumping can also be applied to parallelize many other graph algorithms including connected components, minimum spanning trees, and biconnected components.
  • It is relatively straightforward to parallelize a number of steps in ABC algorithms based on rejection sampling and sequential Monte Carlo methods.
  • Next »