Overconcurrentie

Overconcurrentie is a term from Dutch informatics that describes a state in which a system or application creates more concurrent tasks than its resources can efficiently handle. The concept is closely related to the well–known principle of scalability limits and the Addison–Wesley performance model, which shows that adding threads or processes does not always lead to linear speedup. When the number of concurrent units—such as threads, coroutines, or jobs—exceeds the saturation point of the CPU cores, memory bandwidth, or I/O subsystems, the system incurs excessive context switching, lock contention, and cache invalidation. The overall throughput can even degrade, a phenomenon sometimes called “thread thrashing” or “hot swapping”.

Typical scenarios include web servers that spawn a thread per connection without thread pooling, or Map‑Reduce frameworks that launch an overwhelming number of map tasks on a limited number of worker nodes. Overconcurrentie can also appear in real‑time data pipelines where too many consumer processes drain a shared message queue, causing back‑pressure and stalling producers.

The primary indicator of overconcurrentie is a diminishing return curve: initially, adding worker units increases throughput, but after a peak the metric plateaus or declines. Tools such as profilers, performance counters, and queue depth monitors help detect the saturation point. Mitigation strategies involve applying the “Law of the Minimum” – match concurrency to actual hardware limits, use back‑pressure protocols, or employ adaptive thread pools that grow and shrink based on current load.

In practice, designing for optimal concurrency requires a balance: enough parallelism to exploit available resources, but not so much that contention overtakes parallelism. Overconcurrentie remains a key consideration for developers targeting high‑performance, multi‑core, or distributed systems.