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Fine-Grained Multi-Query Stream Processing on Integrated Architectures
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DOI：10.1109/TPDS.2021.3066407.png)
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Abstract
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Exploring the sharing opportunities among multiple stream queries is crucial for high-performance stream processing. Modern stream processing necessitates accelerating multiple queries by utilizing heterogeneous coprocessors, such as GPUs, and this has shown to be an effective method. Emerging CPU-GPU integrated architectures 6integrate CPU and GPU on the same chip and eliminate PCI-e bandwidth bottleneck. Such a novel architecture provides new opportunities for improving multi-query performance in stream processing but has not been fully explored by existing systems. We introduce a stream processing engine, called FineStream, for efficient multi-query window-based stream processing on CPU-GPU integrated architectures. FineStream's key contribution is a novel fine-grained workload scheduling mechanism between CPU and GPU to take advantage of both architectures. Particularly, FineStream is able to efficiently handle multiple queries in both static and dynamic streams. Our experimental results show that 1) on integrated architectures, FineStream achieves an average 52 percent throughput improvement and 36 percent lower latency over the state-of-the-art stream processing engine; 2) compared to the coarse-grained strategy of applying different devices for multiple queries, FineStream achieves 32 percent throughput improvement; 3) compared to the stream processing engine on the discrete architecture, FineStream on the integrated architecture achieves 10.4x price-throughput ratio, 1.8x energy efficiency, and can enjoy lower latency benefits.
Keywords:
Computer architecture
Graphics processing units
Structured Query Language
Performance evaluation
Throughput
Engines
Bandwidth
Fine-grained
multi-query
stream processing
CPU
GPU
integrated architectures
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