Advanced

Finding fast action selectors for dataflow actors

Cedersjö, Gustav LU ; Janneck, Jörn LU and Skeppstedt, Jonas LU (2014) 48th Asilomar Conference on Signals, Systems and Computers, 2014 In [Host publication title missing] p.1435-1439
Abstract
The parallel structure of dataflow programs and their support for processing streams of data make dataflow programming an interesting tool for doing stream processing on parallel processing architectures. The computational kernels, the actors, of a dataflow program communicate with other actors via FIFO channels. The actors in the dataflow model used in this paper may perform different actions depending on the state of the actor and on the data that has been sent to the actor that is present on its ingoing channels. For this kind of dataflow programs, decisions on what to do in an actor in a given state has to be made at runtime in a process called action selection. Each action is associated with a set of conditions on the state and the... (More)
The parallel structure of dataflow programs and their support for processing streams of data make dataflow programming an interesting tool for doing stream processing on parallel processing architectures. The computational kernels, the actors, of a dataflow program communicate with other actors via FIFO channels. The actors in the dataflow model used in this paper may perform different actions depending on the state of the actor and on the data that has been sent to the actor that is present on its ingoing channels. For this kind of dataflow programs, decisions on what to do in an actor in a given state has to be made at runtime in a process called action selection. Each action is associated with a set of conditions on the state and the input channels. All conditions must be fulfilled for the action to be selected, and the task of the action selector is to test different conditions to select an action. This paper builds upon previous work on the actor machine - a machine model for dataflow actors where the action selection is central. We present two heuristics that based on profiling data creates fast action selectors using the actor machine. The heuristics are implemented in the Tÿcho Dataflow Compiler and are evaluated using a video decoder written in Cal. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[Host publication title missing]
pages
1435 - 1439
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
48th Asilomar Conference on Signals, Systems and Computers, 2014
external identifiers
  • Scopus:84940483461
ISBN
978-1-4799-8295-0
DOI
10.1109/ACSSC.2014.7094699
language
English
LU publication?
yes
id
89ada92a-e6f3-4711-a75b-41bf989ca83d (old id 7866097)
date added to LUP
2015-09-14 11:23:03
date last changed
2016-10-13 04:50:51
@misc{89ada92a-e6f3-4711-a75b-41bf989ca83d,
  abstract     = {The parallel structure of dataflow programs and their support for processing streams of data make dataflow programming an interesting tool for doing stream processing on parallel processing architectures. The computational kernels, the actors, of a dataflow program communicate with other actors via FIFO channels. The actors in the dataflow model used in this paper may perform different actions depending on the state of the actor and on the data that has been sent to the actor that is present on its ingoing channels. For this kind of dataflow programs, decisions on what to do in an actor in a given state has to be made at runtime in a process called action selection. Each action is associated with a set of conditions on the state and the input channels. All conditions must be fulfilled for the action to be selected, and the task of the action selector is to test different conditions to select an action. This paper builds upon previous work on the actor machine - a machine model for dataflow actors where the action selection is central. We present two heuristics that based on profiling data creates fast action selectors using the actor machine. The heuristics are implemented in the Tÿcho Dataflow Compiler and are evaluated using a video decoder written in Cal.},
  author       = {Cedersjö, Gustav and Janneck, Jörn and Skeppstedt, Jonas},
  isbn         = {978-1-4799-8295-0},
  language     = {eng},
  pages        = {1435--1439},
  publisher    = {ARRAY(0xa1944d0)},
  series       = {[Host publication title missing]},
  title        = {Finding fast action selectors for dataflow actors},
  url          = {http://dx.doi.org/10.1109/ACSSC.2014.7094699},
  year         = {2014},
}