How Efficient is Go\'s Garbage Collection with Terabytes of RAM?

Go Garbage Collection Performance with Terabytes of RAM

The Go programming language has faced limitations when handling large amounts of RAM, particularly due to prolonged GC pauses. With the introduction of the new Go garbage collector in version 1.5, concerns arise about its efficiency in managing terabytes of memory.

Are there any benchmarks regarding this improvement?

While benchmarks are scarce, some observations have been made:

• Go processes cannot currently utilize more than 512 GB of RAM (Linux). The maximum tested heap size is approximately 240 GB.
• The Go GC prioritizes reducing GC pauses rather than overall workload.
• Longer GC pauses typically occur when fewer pointers, higher allocation rates, and less available RAM are present.

Implications for Usage:

Although the improved GC reduces pause times, it doesn't eliminate the workload. Applications running with TBs of RAM, especially those with substantial pointer usage and allocation rates, may still experience significant GC impact.

Alternative Solutions:

For situations where GC scalability is critical, consider:

• Employing low-level languages like C .
• Outsourcing bulky data to external services such as embedded databases or caching systems.
• Deploying multiple processes with smaller heap sizes instead of a single large one.
• Implementing thorough testing and optimizations to prevent memory-related issues.

Additional Information:

• GC workload can be conceptualized as the multiplication of pointers, allocation rate, and the inverse of spare RAM.
• Prior to Go 1.5, pausing was triggered by scanning pointers on the stack and in globals.
• Go 1.6 further optimized background work, reducing pauses with heaps up to 200GB.
• Go 1.8 alleviated most pauses below 1ms by handling stack scanning separately from global pauses.

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