Task allocation in data flow multiprocessors: an annotated bibliography

Authors:
Camille C. Price
Affiliations:
Computer Science Department, Stephen F. Austin State University, Nacogdoches, Texas
Venue:
ACM SIGARCH Computer Architecture News - Symposium on parallel algorithms and architectures
Year:
1991

Citing 10
Cited 0

The Manchester prototype dataflow computer

Communications of the ACM - Special section on computer architecture
Data flow computing

Data flow computing
A Fault-Tolerant Dataflow System

Computer
A Formal Definition of Data Flow Graph Models

IEEE Transactions on Computers
Static scheduling of synchronous data flow programs for digital signal processing

IEEE Transactions on Computers
Dataflow machine architecture

ACM Computing Surveys (CSUR)
Efficient computation of dataflow graphs in a hypercube architecture

Computer Systems Science and Engineering
The effect of operation scheduling on the performance of a data flow computer

IEEE Transactions on Computers
Demand-Driven Interpretation of FP Programs on a Data-Flow Multiprocessor

IEEE Transactions on Computers - Special issue on architectural support for programming languages and operating systems
A Data-Driven VLSI Array for Arbitrary Algorithms

Computer

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Abstract

The performance of data flow multiprocessors depends to a large extent on the methods used to partition a data flow program and assign the resulting computational tasks among the processors. We cite significant contributions to the field of data flow computing, and categorize these efforts according to the granularity of the partitions and by whether task allocation is static (performed at compile time) or dynamic (performed during execution of the program). Each reference is accompanied by a brief description of the task allocation techniques used in the system.