Program equivalence and context-free grammars
Barry K. Rosen
SWAT 1972
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.
Barry K. Rosen
SWAT 1972
Michael Hersche, Mustafa Zeqiri, et al.
NeSy 2023
Salvatore Certo, Anh Pham, et al.
Quantum Machine Intelligence
Vicki L Hanson, Edward H Lichtenstein
Cognitive Psychology