There is no single, universal number for how many threads are "safe." The optimal and "safe" number of threads largely depends on the specific task being performed, the available system resources (like CPU cores and memory), and what "safe" means in your context – typically focusing on performance and resource usage rather than preventing crashes or deadlocks, which require careful programming practices regardless of thread count.
It Depends on Your Task: CPU vs. IO
Understanding the nature of the work your threads will do is crucial:
- CPU-Bound Tasks: These tasks spend most of their time performing calculations and consuming CPU cycles. Examples include heavy data processing, complex computations, or rendering.
- IO-Bound Tasks: These tasks spend most of their time waiting for external operations to complete, such as reading from a disk, making network requests, or waiting for user input. During this waiting period, the CPU is often idle and can switch to another thread.
Finding the Right Thread Count
The ideal number of threads differs significantly between these two types of tasks:
- For CPU-bound tasks, a common guideline is to use a number of threads roughly equal to the number of available CPU cores. Using significantly more threads than cores can lead to excessive context switching overhead, where the operating system spends more time managing threads than executing work, degrading performance.
- For IO-bound tasks, you can often use more threads than CPU cores. While one thread waits for an IO operation, another thread can use the CPU. The "safe" or optimal number depends on the ratio of waiting time to computing time.
A Specific Example for IO-Bound Tasks
Based on testing highlighted in the reference:
- For code identified as fully IO-bound running on a specific machine, performance was tested with varying thread counts.
- The performance "sweet spot" was found to be around 10 threads.
- Increasing the number of threads beyond 10 did not result in further performance improvement.
- Using more than 10 threads in this scenario simply consumed more resources.
- In some cases, utilizing a higher number of threads (up to 30 were tested) actually led to worse performance.
This example illustrates that for IO-bound workloads, there's a point of diminishing returns. Adding more threads past this point doesn't speed up the work because the bottleneck isn't CPU power but the speed of the IO operations. Additional threads just add overhead.
Considerations for "Safety"
Beyond performance, "safe" also implies not exhausting system resources. Each thread consumes memory (for its stack and other data), and managing a large number of threads incurs CPU overhead due to scheduling and context switching. Using too many threads can lead to:
- High memory consumption
- Increased CPU usage for thread management
- Degraded overall system responsiveness
In summary, determining a "safe" number of threads requires considering your workload (CPU vs. IO), your hardware, and testing to find the point where adding more threads no longer provides a benefit and potentially harms performance or wastes resources, as demonstrated by the 10 threads sweet spot observed for a specific IO-bound case in the reference.
