Ruby MRI thread and performance

Question

My first question is about SO, but I have been hiding for a long time, so you have to forgive me if I break any rules or post a garbage question.

I'm trying to better understand the flows, and I decided to test the MRI and see how it works in general.

Given the following code (and output), why are multithreaded operations much slower than the non-threaded version?

code

class Benchmarker
  def self.go
    puts '----------Benchmark Start----------'
    start_t = Time.now
    yield
    end_t = Time.now
    puts "Operation Took: #{end_t - start_t} seconds"
    puts '----------Benchmark End------------'
  end
end

# using mutex
puts 'Benchmark 1 (threaded, mutex):'
Benchmarker.go do
  array = []
  mutex = Mutex.new
  5000.times.map do
    Thread.new do
      mutex.synchronize do
        1000.times do
          array << nil
        end
      end
    end
  end.each(&:join)
  puts array.size
end

# using threads
puts 'Benchmark 2 (threaded, no mutex):'
Benchmarker.go do
  array = []
  5000.times.map do
    Thread.new do
      1000.times do
        array << nil
      end
    end
  end.each(&:join)
  puts array.size
end

# no threads
puts 'Benchmark 3 (no threads):'
Benchmarker.go do
  array = []
  5000.times.map do
    1000.times do
      array << nil
    end
  end
  puts array.size
end

output

Benchmark 1 (threaded, mutex):
----------Benchmark Start----------
5000000
Operation Took: 3.373886 seconds
----------Benchmark End------------
Benchmark 2 (threaded, no mutex):
----------Benchmark Start----------
5000000
Operation Took: 5.040501 seconds
----------Benchmark End------------
Benchmark 3 (no threads):
----------Benchmark Start----------
5000000
Operation Took: 0.454665 seconds
----------Benchmark End------------

Thanks in advance.

Answer 1

(5000), , . , 30-50 .

, :

  20.times.map do
    Thread.new do
      250000.times do
        array << nil
      end
    end
  end.each(&:join)

.

, , , Time(threaded) >= Time(non-threaded) - Threaded, . - MRI GIL, ( ). Ruby, JRuby, .