Amy Lin, Sujit Roy, et al.
AGU 2024
High-performance stream processing is critical in many sense-and-respond application domainsfrom environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high-rate live streams. The central tenets of this work are the programming model, the workload splitting mechanisms, the code generation framework, and the underlying System S middleware and Spade programming model. We demonstrate considerable scalability behavior coupled with low processing latency in a real-world financial trading application. © 2010 Elsevier Inc. All rights reserved.
Amy Lin, Sujit Roy, et al.
AGU 2024
Zijian Ding, Michelle Brachman, et al.
C&C 2025
David Carmel, Haggai Roitman, et al.
ACM TIST
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IJCAI 2024