The phrase "achieve parallelism" is correct and usable in written English.
It can be used in contexts related to writing, programming, or any field where balance and symmetry in structure or design are important.
Example: "To enhance the clarity of your writing, it is essential to achieve parallelism in your lists and comparisons."
Alternatives: "establish parallel structure" or "create symmetry".
As described above, each functional module is replicated and executed in parallel to achieve parallelism.
This fact can be largely taken advantage of in order to achieve parallelism by existing workflow management approaches emphasizing parallelization.
Although MapReduce provides basic functionality for many data processing operations, users are limited since they need to adapt their applications to the MapReduce model to achieve parallelism.
In order to achieve parallelism, framework library splits the huge input data set into multiple chunks of typically 16 64 MB based on configuration provided [34].
In order to achieve parallelism wherever applicable relies on partitioning input string into smaller segments and construct subtrees for each of such segment.
The significance of this additional osteotomy was to enable a proximal valgus osteotomy large enough to eradicate any degree of adduction in the hip (and thereby eliminate the Trendelenburg gait) but, through the distal varus osteotomy, achieve parallelism of both legs.
It is well known that a high level of parallelization can be achieved in a plethora of bioinformatics workflows by fragmenting the input of individual processes into chunks and processing them independently, thus achieving parallelism in an embarrassingly parallel way.
In [13, 22, 23], authors have achieved parallelism by splitting input string into smaller units and processing them in parallel to produce intermediate trees on disk.
Typically, these applications suffer from significant variability in the interplay between achieved parallelism and data footprint.
Evidently, a mechanism for achieving parallelism in the execution of an OU pipeline in a single site is required.
The UCF uses a non-traditional approach to achieving parallelism, employing an abstract taskgraph representation to describe computation and communication.
