Self-Adaptive Micro-Batching for Low-Latency GPU-Accelerated Stream Processing

Stream processing is a computing paradigm enabling the continuous processing of unbounded data streams. Some classes of stream processing applications can greatly benefit from the parallel processing power and affordability offered by GPUs. However, efficient GPU utilization with stream processing a...

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Vydané v:	International journal of parallel programming Ročník 53; číslo 2; s. 14
Hlavní autori:	Leonarczyk, Ricardo, Mencagli, Gabriele, Griebler, Dalvan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.04.2025 Springer Nature B.V
Predmet:	Adaptive algorithms Algorithms Computer Science Data transfer (computers) Data transmission Effectiveness Graphics processing units Parallel processing Processor Architectures Segments Self adaptive control systems Software Engineering/Programming and Operating Systems Theory of Computation Workload Workloads Parallel programming GPU programming Self-adaptive algorithms Heterogeneous architectures
ISSN:	0885-7458, 1573-7640
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