Masami Akamine, Jitendra Ajmera
IEICE Trans Inf Syst
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.
Masami Akamine, Jitendra Ajmera
IEICE Trans Inf Syst
S. Winograd
Journal of the ACM
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
Joxan Jaffar
Journal of the ACM