Monsoon

Author:

Papadopoulos Gregory M.1,Culler David E.2

Affiliation:

1. Laboratory for Computer Science, Massachusetts Institute of Technology

2. Computer Science Division, University of California, Berkeley

Abstract

Dataflow architectures tolerate long unpredictable communication delays and support generation and coordination of parallel activities directly in hardware, rather than assuming that program mapping will cause these issues to disappear. However, the proposed mechanisms are complex and introduce new mapping complications. This paper presents a greatly simplified approach to dataflow execution, called the explicit token store (ETS) architecture, and its current realization in Monsoon . The essence of dynamic dataflow execution is captured by a simple transition on state bits associated with storage local to a processor. Low-level storage management is performed by the compiler in assigning nodes to slots in an activation frame , rather than dynamically in hardware. The processor is simple, highly pipelined, and quite general. It may be viewed as a generalization of a fairly primitive von Neumann architecture. Although the addressing capability is restrictive, there is exactly one instruction executed for each action on the dataflow graph. Thus, the machine oriented ETS model provides new understanding of the merits and the real cost of direct execution of dataflow graphs.

Publisher

Association for Computing Machinery (ACM)

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Revet: A Language and Compiler for Dataflow Threads;2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA);2024-03-02

2. Improving Utilization of Dataflow Unit for Multi-Batch Processing.;ACM Transactions on Architecture and Code Optimization;2023-12-18

3. DiAG: a dataflow-inspired architecture for general-purpose processors;Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems;2021-04-17

4. A task-uncoordinated distributed dataflow model for scalable high performance parallel program execution;Parallel Computing;2016-01

5. HPX;Proceedings of the 8th International Conference on Partitioned Global Address Space Programming Models - PGAS '14;2014

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