2000
DOI: 10.1145/346152.346320
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Analysis of optimal thread pool size

Abstract: The success of e-commerce, messaging middleware, and other Internet-based applications depends in part on the ability of network servers to respond in a timely and reliable manner to simultaneous service requests. Multithreaded systems, due to their efficient use of system resources and the popularity of shared-memory multi-processor architectures, have become the server implementation of choice. However, creating and destroying a thread is far from free, requiring run-time memory allocation and deallocation. … Show more

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Cited by 55 publications
(26 citation statements)
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“…Each analysis event maps to a thread that consumes memory to maintain its stack, utilizes the processor to run the lookup and the analysis processes, and incurs additional overhead resulting from thread context switches. For the computations, we suppose that the lookup process takes T l seconds to execute, the analysis process takes T a seconds, and each thread incurs a context switch of c a seconds, while thread creation and destruction overheads can be ignored as they are in the order of microseconds [32]. c) The query execution process responds to client (user or application) queries that aim to get a view of traffic flows involving certain Web servers.…”
Section: Base Server Scalabilitymentioning
confidence: 99%
“…Each analysis event maps to a thread that consumes memory to maintain its stack, utilizes the processor to run the lookup and the analysis processes, and incurs additional overhead resulting from thread context switches. For the computations, we suppose that the lookup process takes T l seconds to execute, the analysis process takes T a seconds, and each thread incurs a context switch of c a seconds, while thread creation and destruction overheads can be ignored as they are in the order of microseconds [32]. c) The query execution process responds to client (user or application) queries that aim to get a view of traffic flows involving certain Web servers.…”
Section: Base Server Scalabilitymentioning
confidence: 99%
“…Algorithms try to dynamically decide what is the optimal number of active threads to sustain required high performance. However, proposals that deal with native threads try to minimize the number of idle threads to reduce management overhead [12,13]. Our proposal is based on the fact that Web Workers run in a browser's virtual machine.…”
Section: Dynamic Web Worker Pool Managermentioning
confidence: 99%
“…A high volume of service requests results in frequent memory allocation and deallocation, and becomes a major factor in performance bottleneck [8]. Under thread pool technology, maintaining threads in the pool incurs a run-time overhead for all tasks.…”
Section: Pool Technology 1) Thread Poolmentioning
confidence: 99%