Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
StreamIt: A Language for Streaming Applications
CC '02 Proceedings of the 11th International Conference on Compiler Construction
MPICH-G2: a Grid-enabled implementation of the Message Passing Interface
Journal of Parallel and Distributed Computing - Special issue on computational grids
Cg: a system for programming graphics hardware in a C-like language
ACM SIGGRAPH 2003 Papers
Programmable Stream Processors
Computer
Evaluating the Imagine Stream Architecture
Proceedings of the 31st annual international symposium on Computer architecture
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
ACM SIGMOD Record
Stream Programming on General-Purpose Processors
Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture
The 8 requirements of real-time stream processing
ACM SIGMOD Record
Proceedings of the 4th international conference on Computing frontiers
A grid-aware MIP solver: Implementation and case studies
Future Generation Computer Systems
Streamflex: high-throughput stream programming in java
Proceedings of the 22nd annual ACM SIGPLAN conference on Object-oriented programming systems and applications
A lightweight stream-processing library using MPI
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Designing multi-leader-based Allgather algorithms for multi-core clusters
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
A streaming machine description and programming model
SAMOS'07 Proceedings of the 7th international conference on Embedded computer systems: architectures, modeling, and simulation
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The MPI programming model hides network type and topology from developers, but also allows them to seamlessly distribute a computational job across multiple cores in both an intra and inter node fashion. This provides for high locality performance when the cores are either on the same node or on nodes closely connected by the same network type. The streaming model splits a computational job into a linear chain of decoupled units. This decoupling allows the placement of job units on optimal nodes according to network topology. Furthermore, the links between these units can be of varying protocols when the application is distributed across a heterogeneous network. In this paper we study how to integrate the MPI and Stream programming models in order to exploit network locality and topology. We present a hybrid MPI-Stream framework that aims to take advantage of each model's strengths. We test our framework with a financial application. This application simulates an electronic market for a single financial instrument. A stream of buy and sell orders is fed into a price matching engine. The matching engine creates a stream of order confirmations, trade confirmations, and quotes based on its attempts to match buyers with sellers. Our results show that the hybrid MPI-Stream framework can deliver a 32% performance improvement at certain order transmission rates.