Get to know Parallelizing better with 2 real example sentences, the meaning.
Parallelizing in a sentence
Parallelizing meaning
present participle and gerund of parallelize
Using Parallelizing
- The main meaning on this page is: present participle and gerund of parallelize
Context around Parallelizing
- Average sentence length in these examples: 16.5 words
- Position in the sentence: 1 start, 0 middle, 1 end
- Sentence types: 2 statements, 0 questions, 0 exclamations
Corpus analysis for Parallelizing
- In this selection, "parallelizing" usually appears near the start of the sentence. The average example has 16.5 words, and this corpus slice is mostly made up of statements.
- Around the word, transactions and compiler stand out and add context to how "parallelizing" is used.
- Recognizable usage signals include and in parallelizing compiler techniques and by parallelizing transactions polkadot. That gives this page its own corpus information beyond isolated example sentences.
- By corpus frequency, "parallelizing" sits close to words such as aabc, aacr and aacsb, which helps place it inside the broader word index.
Example types with parallelizing
The same corpus examples are grouped by length and sentence type, making it easier to see the contexts in which the word appears:
By parallelizing transactions, Polkadot solves major scalability issues that have thus far hampered blockchain development. (15 words)
Another application of these transformations is in compiler optimizations of nested-loop code, and in parallelizing compiler techniques. (18 words)
Another application of these transformations is in compiler optimizations of nested-loop code, and in parallelizing compiler techniques. (18 words)
By parallelizing transactions, Polkadot solves major scalability issues that have thus far hampered blockchain development. (15 words)
Example sentences (2)
By parallelizing transactions, Polkadot solves major scalability issues that have thus far hampered blockchain development.
Another application of these transformations is in compiler optimizations of nested-loop code, and in parallelizing compiler techniques.