text: Q:
  
  relationship between computer logical cores and nodejs threadpool
  
  I have read lots of articles on stackoverflow, but failed to find any references about relationship between computer`s logical cores and nodejs threadpool. I believe this is not the duplicated question.
  I am using 2017 macbook pro which has 2physical core with 4threads(4 logical cores)
  and I believe that nodejs uses threadpool size of 4 (reference with libuv) when doing heavy stuffs such as pbkdf2(function inside of crypto module), i/o operations.
  my question is that, what is the relationship between computer's thread size and nodejs's threadpool size?
  actually I have never thought about the computer's thread.
  it may sound crazy but so far I believed computer only has physical core, and if application such as nodejs instance supports thread pool(in this case thread pool size of 4 by default), then computer can utilize multi-threading.
  so what exactly is the relationship between those two?
  do I have to change THREADPOOL_SIZE to number of computer's logical core to maximize the performance..?
  
  A:
  
  node.js does not dynamically adjust the threadpool size based on the CPUs or logical CPUs that are present.  It has a preset value (4) unless you customize it.
  Because the threadpool is often used for blocking operations such as disk I/O, it's not necessarily true that an optimal value for the thread pool size is the number of logical CPUs you have (unlike the typical recommendation for clustering).  
  Instead, it would likely depend upon which specific types of operations you most want to optimize for and exactly how you're using those operations.  For example, it probably doesn't really help you a lot to make more and more parallel disk operations that are all trying to access the same physical disk because there's only one position the read/write head can move at a time so having lots of parallel operations all contending for the same read/write head may not speed things up (could even make things slower).
  If you have a specific operation you're trying to optimize for, then your best bet is to create a reproducible benchmark test and then time it with several different sizes for the thread pool.
  As was pointed out in a comment, you can study some of the relevant thread pool code here.
  
  