What is the fastest language for multithreading?

Multithreading can provide major performance improvements by allowing multiple threads to execute code concurrently. However, realizing the full benefits requires choosing an optimal language and effectively managing thread usage. This guide explores the fastest languages for multithreading and key optimization techniques.

What Makes a Language Fast for Multithreading?

Several factors influence multithreading speed:

The Contenders: C++, Java, and Go

Based on the criteria above, top choices are:

Honorable Mentions

Key Optimization Techniques

Here are 5 key ways to get maximum multithreading performance in your code:

1. Size thread pools: Creating threads has overhead. Reuse thread pools rather than continually creating threads. But beware of resource contention with too few threads.
2. Minimize shared state: More shared state means more locking overhead to prevent data races. Design code to minimize sharing where possible.
3. Avoid unnecessary blocking: Blocking threads slows everything down. Only block where absolutely necessary and minimize blocking time.
4. Scale up and down: Scale thread pools based on workload demands to right-size resource usage. Concurrency limits can automatically handle scaling threads.
5. Profile and tune: Profile on target deployment platforms to catch thread contention issues. Tune concurrency limits and pools over time.

Here is Go code optimizing a thumbnail generator with the techniques above:

// Size thread pool 
var throttle = make(chan int, 100) 

func generateThumbnails() {

  for _, img := range images {
    
    // Minimize blocking 
    go func(img Image) {
        
        // Avoid shared state
        dst := createEmptyThumbnail() 
        
        // Scale thread usage
        throttle <- 1
        defer func() { <-throttle }()
        
        // Do work
        generateThumbnail(img, dst)
    }(img)
  } 
}

Key Takeaways

The right language and optimization provides large multithreading speedups. Consider starting with Go for its simple concurrency model before scaling up to Java or C++. Profile across platforms and workloads to ensure scaling threads maximizes real world performance.